adventofcode2020.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Jeremynadal33/adventofcode2020/blob/master/adventofcode2020.ipynb)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import numpy as np\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "root_dir = '/Users/jeremynadal/Documents/adventofcode/adventofcode2020/'\n",
    "file_path = root_dir + 'inputs/input_3.txt'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 2 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(root_dir+'input_2.txt',sep = '\\n', header = None)\n",
    "data.columns = ['raw']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1-4', 'm:', 'mrfmmbjxr']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['raw'][0].split(' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "check = []\n",
    "\n",
    "for ind in range(data.shape[0]):\n",
    "    min_letter = int(data['raw'][ind].split(' ')[0].split('-')[0])\n",
    "    max_letter = int(data['raw'][ind].split(' ')[0].split('-')[1])\n",
    "    letter     = data['raw'][ind].split(' ')[1].split(':')[0]\n",
    "    passcode   = data['raw'][ind].split(' ')[2]\n",
    "\n",
    "    check.append( (passcode.count(letter)<=max_letter) and  (passcode.count(letter)>=min_letter))\n",
    "    \n",
    "data['check'] = check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "607"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['check'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "check = []\n",
    "for ind in range(data.shape[0]):\n",
    "    first_letter = int(data['raw'][ind].split(' ')[0].split('-')[0])\n",
    "    second_letter = int(data['raw'][ind].split(' ')[0].split('-')[1])\n",
    "    letter     = data['raw'][ind].split(' ')[1].split(':')[0]\n",
    "    passcode   = data['raw'][ind].split(' ')[2]\n",
    "\n",
    "    check.append( (passcode[first_letter-1]==letter or passcode[second_letter-1]==letter ) \n",
    "                 and not (passcode[first_letter-1]==letter and passcode[second_letter-1]==letter ) )\n",
    "data['check'] = check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "321"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['check'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(323, 31)\n"
     ]
    }
   ],
   "source": [
    "file = 'input_3.txt'\n",
    "with open(root_dir+file,\"rt\") as infile:\n",
    "    data =  np.matrix([list(line.strip()) for line in infile.readlines()])\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'.'"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape\n",
    "data[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "direction : [1, 1]\n",
      "[322, 12] 60\n",
      "direction : [1, 3]\n",
      "[322, 5] 286\n",
      "direction : [1, 5]\n",
      "[322, 29] 76\n",
      "direction : [1, 7]\n",
      "[322, 22] 62\n",
      "direction : [2, 1]\n",
      "[322, 6] 45\n",
      "3638606400\n"
     ]
    }
   ],
   "source": [
    "mult = 1\n",
    "directions = [[1,1],[1,3],[1,5],[1,7],[2,1]] # One down and three right\n",
    "\n",
    "for direction in directions : \n",
    "    print('direction :',direction)\n",
    "    pos = [0,0]\n",
    "    trees = 0\n",
    "    while pos[0] < (data.shape[0]-1) : \n",
    "        pos[0] += direction[0]\n",
    "        pos[1] += direction[1]\n",
    "        if pos[1] >= data.shape[1]:\n",
    "            pos[1] = pos[1] - data.shape[1]\n",
    "        if data[pos[0],pos[1]] == '#':\n",
    "            trees += 1\n",
    "    mult *= trees\n",
    "        \n",
    "    print(pos,trees)\n",
    "print(mult)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = root_dir+'inputs/input_4.txt'\n",
    "\n",
    "if os.path.exists(file_path):\n",
    "    file = open(file_path,'r')\n",
    "    \n",
    "raw = file.read()\n",
    "raw = raw[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = raw.split('\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = [re.sub('\\n',' ',r) for r in raw ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ecl:hzl byr:1926 iyr:2010 pid:221225902 cid:61 hgt:186cm eyr:2021 hcl:#7d3b0c',\n",
       " 'hcl:#efcc98 hgt:178 pid:433543520 eyr:2020 byr:1926 ecl:blu cid:92 iyr:2010',\n",
       " 'iyr:2018 eyr:2026 byr:1946 ecl:brn hcl:#b6652a hgt:158cm pid:822320101',\n",
       " 'iyr:2010 hgt:138 ecl:grn pid:21019503 eyr:1937 byr:2008 hcl:z',\n",
       " 'byr:2018 hcl:z eyr:1990 ecl:#d06796 iyr:2019 hgt:176in cid:75 pid:153cm',\n",
       " 'byr:1994 hcl:#ceb3a1 hgt:176cm cid:80 pid:665071929 eyr:2024 iyr:2020 ecl:grn',\n",
       " 'cid:280 byr:1955 ecl:blu hgt:155cm hcl:#733820 eyr:2013 iyr:2011 pid:2346820632',\n",
       " 'hcl:#4a5917 hgt:61cm pid:4772651050 iyr:2026 ecl:brn byr:2015 eyr:2026',\n",
       " 'iyr:2019 hcl:#a97842 hgt:182cm eyr:2024 ecl:gry pid:917294399 byr:1974',\n",
       " 'ecl:#9c635c pid:830491851 hgt:175cm cid:141 iyr:2010 hcl:z byr:2026 eyr:1998',\n",
       " 'byr:1927 iyr:2011 pid:055176954 ecl:gry hcl:#7d3b0c eyr:2025 hgt:166cm',\n",
       " 'hcl:#733820 byr:2008 ecl:utc eyr:1920 pid:159cm hgt:66cm iyr:2030',\n",
       " 'pid:027609878 eyr:2022 iyr:2012 byr:1960 hgt:157cm hcl:#b6652a cid:117 ecl:grn',\n",
       " 'iyr:2025 pid:7190749793 ecl:grn byr:1984 hgt:71in hcl:c41681 cid:259 eyr:1928',\n",
       " 'eyr:2029 pid:141655389 cid:52 hcl:#cfa07d iyr:2019 ecl:blu hgt:69in byr:1938',\n",
       " 'eyr:2020 hgt:166cm ecl:gry pid:611660309 iyr:2011 hcl:#623a2f byr:1943',\n",
       " 'hgt:190cm eyr:2022 byr:2000 cid:210 pid:728418346 hcl:#a97842 ecl:xry iyr:2015',\n",
       " 'byr:1973 eyr:2028 iyr:2012 hcl:#ff0ec8 pid:740554599 ecl:amb cid:58 hgt:155cm',\n",
       " 'iyr:2016 pid:922938570 ecl:oth hcl:#fffffd hgt:154cm eyr:2021 byr:1966',\n",
       " 'ecl:amb byr:1929 hcl:#c3bbea pid:511876219 iyr:2019 hgt:191cm eyr:2026',\n",
       " 'ecl:utc hgt:155cm pid:#9f0a41 iyr:2012 hcl:#bd4141 byr:1998 eyr:2020',\n",
       " 'ecl:grn hgt:173cm cid:321 pid:851120816 byr:1968 hcl:#a97842 eyr:2027 iyr:2014',\n",
       " 'hgt:155cm hcl:#f40d77 pid:038224056 byr:1953 ecl:brn iyr:2014 eyr:2022',\n",
       " 'pid:181869721 iyr:2011 hgt:151cm hcl:#733820 cid:110 ecl:blu byr:1931 eyr:2024',\n",
       " 'byr:1948 hcl:#888785 hgt:74in cid:112 ecl:hzl pid:921761213 eyr:2028 iyr:2015',\n",
       " 'ecl:gry byr:1931 pid:600127430 hcl:#341e13 eyr:2027 iyr:2013 hgt:173cm',\n",
       " 'hgt:178cm pid:530791289 hcl:#6b5442 eyr:2022 byr:1979 iyr:2014 ecl:hzl',\n",
       " 'pid:412193170 hcl:#cfa07d hgt:186cm iyr:2012 cid:284 eyr:2020 byr:1967 ecl:grn',\n",
       " 'hcl:#6b5442 iyr:2015 pid:808448466 ecl:blu eyr:2022 hgt:159cm byr:1969',\n",
       " 'eyr:2020 iyr:2019 hgt:170cm pid:8964201562 hcl:#6b5442 byr:1947 ecl:amb',\n",
       " 'eyr:2029 ecl:hzl hcl:#866857 byr:1961 iyr:2017',\n",
       " 'ecl:#3456ba eyr:2013 iyr:2020 pid:378280953 hcl:z hgt:174cm',\n",
       " 'hgt:172cm cid:202 ecl:oth eyr:2021 byr:1980 iyr:2012 hcl:#cfa07d pid:605707698',\n",
       " 'cid:281 hgt:161cm iyr:2017 pid:122936432 hcl:#602927 byr:1981 ecl:gry eyr:2021',\n",
       " 'byr:1959 hgt:193cm pid:083900241 iyr:2020 eyr:2037 hcl:#623a2f ecl:hzl',\n",
       " 'iyr:2030 hgt:153cm eyr:2022 hcl:#efcc98 cid:131 byr:2016 ecl:hzl pid:64053944',\n",
       " 'hgt:172cm eyr:2025 hcl:#866857 byr:1938 ecl:dne pid:192cm iyr:2014',\n",
       " 'pid:016297574 cid:152 iyr:2015 eyr:2024 hcl:#341e13 byr:1965 hgt:175cm ecl:oth',\n",
       " 'pid:604330171 cid:125 byr:1974 hgt:160cm iyr:2014 eyr:2022 ecl:oth hcl:#6b5442',\n",
       " 'pid:59747275 byr:2027 hgt:145 hcl:1fd71f iyr:1944 eyr:2037 ecl:brn',\n",
       " 'iyr:2010 eyr:2021 byr:1953 pid:7098774146 ecl:brn hcl:98737d hgt:158cm',\n",
       " 'hcl:#602927 eyr:2039 pid:#81a5a1 iyr:2012 cid:67 byr:1951 ecl:#6551f5 hgt:76cm',\n",
       " 'hgt:170cm ecl:oth cid:235 eyr:2022 byr:1929 iyr:2019 hcl:#341e13 pid:797557745',\n",
       " 'iyr:2011 hcl:#733820 eyr:2022 pid:830183476 ecl:blu byr:1976 cid:157 hgt:75in',\n",
       " 'hgt:164cm ecl:amb pid:653425455 hcl:#623a2f byr:1977 eyr:2020 iyr:2013',\n",
       " 'byr:2009 eyr:1953 hgt:178cm pid:#5d02f0 hcl:#a97842 iyr:2016 ecl:amb',\n",
       " 'pid:009643210 eyr:2036 ecl:zzz cid:97 hcl:32e540 byr:2005 hgt:187cm iyr:2021',\n",
       " 'pid:155cm iyr:2022 byr:2024 eyr:2031 ecl:amb cid:79 hcl:#cfa07d hgt:69cm',\n",
       " 'cid:176 ecl:oth pid:688645779 byr:1933 eyr:2026 hgt:69cm iyr:2016 hcl:#888785',\n",
       " 'hcl:#888785 eyr:2027 iyr:2020 pid:802243213 ecl:brn hgt:179cm byr:1976',\n",
       " 'hcl:#6cad3e hgt:164cm byr:1982 iyr:2020 ecl:gry pid:142160687 eyr:2023',\n",
       " 'hcl:#18171d hgt:153cm iyr:2014 ecl:hzl cid:231 pid:167809118 byr:1997 eyr:2028',\n",
       " 'byr:1940 ecl:hzl iyr:2016 cid:67 hcl:#c800da pid:563956960 eyr:2021 hgt:189cm',\n",
       " 'pid:133094996 eyr:2032 hgt:60cm hcl:#623a2f byr:2030 ecl:dne iyr:2023',\n",
       " 'pid:65195409 hcl:d0d492 iyr:1956 byr:2019 ecl:#bb043f eyr:2031 hgt:167in',\n",
       " 'iyr:2016 byr:2006 ecl:#35d62f eyr:2029 hgt:186cm hcl:1d8307',\n",
       " 'eyr:1935 iyr:1960 pid:346667344 ecl:grn hgt:170cm hcl:cfcc36',\n",
       " 'ecl:oth byr:1979 pid:165581192 hgt:177cm hcl:#c0946f iyr:2011',\n",
       " 'iyr:2011 eyr:2030 pid:250840477 byr:1934 cid:174 hgt:179cm hcl:#866857 ecl:blu',\n",
       " 'hgt:157cm hcl:#7d3b0c eyr:2027 pid:979510046 ecl:oth',\n",
       " 'iyr:2025 hgt:69 ecl:grt byr:1935 eyr:1928 pid:168cm cid:271 hcl:z',\n",
       " 'pid:998166233 iyr:2020 hgt:166cm ecl:amb byr:1995 hcl:#fffffd',\n",
       " 'hcl:#ceb3a1 ecl:amb iyr:2019 eyr:2024 hgt:184cm byr:1980 pid:839215481 cid:146',\n",
       " 'byr:1967 pid:444303019 ecl:oth hgt:150cm eyr:2024',\n",
       " 'eyr:2023 byr:1960 iyr:2010 cid:236 hcl:#733820 pid:900635506 hgt:69in ecl:hzl',\n",
       " 'eyr:2029 pid:969574247 hgt:150cm byr:1967 iyr:2010 ecl:blu',\n",
       " 'pid:575879605 iyr:2010 ecl:hzl byr:1963 hgt:151cm hcl:#c0946f cid:277',\n",
       " 'byr:1998 pid:621374275 ecl:brn hcl:z iyr:2029 eyr:2024 hgt:68cm',\n",
       " 'pid:365407169 ecl:amb hcl:#87f433 iyr:2011 eyr:2021 byr:1987 hgt:175cm cid:201',\n",
       " 'hgt:175cm iyr:2020 ecl:gry eyr:2029 pid:806927384 cid:59 byr:1932 hcl:#888785',\n",
       " 'pid:589898274 cid:113 hcl:z hgt:184cm eyr:2000 ecl:lzr iyr:2016 byr:2016',\n",
       " 'ecl:#2bafbb eyr:2038 iyr:2027 hcl:#fffffd hgt:174 byr:2007 pid:093750113',\n",
       " 'eyr:2022 hgt:59in hcl:#ceb3a1 pid:159921662 ecl:gry byr:1948 iyr:2014 cid:50',\n",
       " 'hgt:190cm iyr:2014 pid:480507618 hcl:#fffffd byr:1945 eyr:2029',\n",
       " 'byr:1951 hgt:152cm ecl:brn iyr:2016 eyr:2029 cid:179 pid:027575942 hcl:#fffffd',\n",
       " 'cid:198 pid:728480773 eyr:2028 hgt:153cm iyr:2018 hcl:#888785 ecl:amb byr:1983',\n",
       " 'byr:1968 hcl:#c0946f ecl:grn eyr:2027 iyr:2013 pid:269749807 cid:227 hgt:178cm',\n",
       " 'eyr:2024 hgt:185cm ecl:oth hcl:#448ace byr:1987 iyr:2018 pid:454243136',\n",
       " 'byr:1930 ecl:grn iyr:2018 hgt:158cm hcl:#341e13 eyr:2021',\n",
       " 'eyr:2024 cid:194 pid:425431271 hgt:169cm ecl:grn byr:1973 iyr:2014 hcl:#fffffd',\n",
       " 'ecl:grn cid:110 iyr:2013 hcl:#18171d hgt:155cm eyr:2024 byr:1962 pid:522435225',\n",
       " 'byr:1934 ecl:hzl hgt:152cm iyr:2018 eyr:2024 pid:079740520',\n",
       " 'ecl:grn eyr:2023 hcl:c3f119 pid:468039715 iyr:2013 hgt:150cm byr:1955',\n",
       " 'pid:809357582 eyr:2025 byr:1958 hcl:#6b5442 iyr:2013 hgt:161cm ecl:hzl',\n",
       " 'hcl:#b6652a pid:068979430 byr:1960 iyr:2010 ecl:grn hgt:159cm eyr:2021',\n",
       " 'cid:105 pid:495292692 byr:1965 hcl:#ceb3a1 hgt:160cm ecl:amb iyr:2020',\n",
       " 'iyr:2010 eyr:2024 byr:1941 ecl:grn hcl:#b35770 hgt:171cm cid:132 pid:975699036',\n",
       " 'pid:767448421 hgt:186cm hcl:#733820 byr:1972 iyr:2020 eyr:2026 ecl:grn',\n",
       " 'pid:036236909 iyr:2012 hgt:181cm hcl:#888785 eyr:2026 ecl:hzl byr:1936',\n",
       " 'hgt:173cm byr:1923 ecl:blu eyr:2026 pid:570818321 hcl:#733820 iyr:2016 cid:59',\n",
       " 'pid:2711059768 byr:2024 cid:139 ecl:blu hcl:z hgt:60cm',\n",
       " 'eyr:2025 pid:671193016 byr:1950 hcl:#6b4b25 iyr:2017 hgt:158cm ecl:blu',\n",
       " 'hgt:175cm iyr:2015 ecl:amb byr:1984 eyr:2026 pid:342782894 cid:140',\n",
       " 'iyr:2019 eyr:2027 byr:1972 pid:196266458 hgt:158cm hcl:#7d3b0c cid:69',\n",
       " 'pid:604018034 iyr:2016 ecl:brn eyr:2028 hgt:172cm hcl:#6b5442 byr:1922 cid:238',\n",
       " 'eyr:2024 ecl:gry byr:1970 pid:356551266 cid:340 hgt:162cm iyr:2013',\n",
       " 'ecl:amb hgt:151cm hcl:#18171d byr:1921 pid:187276410 eyr:2030 iyr:2015',\n",
       " 'eyr:2030 pid:056372924 hcl:#d236d9 hgt:156cm iyr:2014 ecl:blu',\n",
       " 'iyr:2014 eyr:2028 byr:1991 hcl:#b6652a pid:119231378 hgt:155cm ecl:blu cid:77',\n",
       " 'hcl:#341e13 eyr:2027 iyr:2012 ecl:grn hgt:152cm pid:405955710 byr:1970',\n",
       " 'iyr:2013 hgt:180cm eyr:1978 ecl:amb byr:1929 pid:3198111997 hcl:z',\n",
       " 'pid:32872520 ecl:#8a0dd4 iyr:1955 eyr:2036 byr:2027 cid:133 hcl:z hgt:184in',\n",
       " 'hgt:152cm pid:402361044 hcl:#efcc98 eyr:2029 ecl:grn iyr:2014 byr:1960',\n",
       " 'byr:1972 eyr:2026 pid:411187543 iyr:2014 hgt:184cm cid:211 hcl:#866857 ecl:brn',\n",
       " 'ecl:brn hcl:#efcc98 pid:311916712 byr:1957 hgt:151cm eyr:2020 iyr:2020',\n",
       " 'iyr:1968 hcl:a28220 pid:#ed250d cid:240 eyr:2031 hgt:181cm ecl:xry',\n",
       " 'ecl:grn byr:1946 hgt:172cm iyr:2010 hcl:#b6652a pid:372011640 eyr:2026',\n",
       " 'ecl:brn eyr:2026 byr:1980 hcl:#c0946f hgt:151cm pid:153076317 iyr:2012',\n",
       " 'byr:1966 pid:852999809 ecl:oth hgt:163cm iyr:2014 eyr:2029 hcl:#341e13',\n",
       " 'ecl:blu byr:1959 hgt:191cm pid:195095631 iyr:2016 hcl:#ceb3a1 eyr:2028',\n",
       " 'byr:2001 ecl:gry hcl:#888785 iyr:2018 hgt:177cm pid:576714115',\n",
       " 'iyr:2017 byr:1949 ecl:blu hgt:186cm cid:289 pid:859016371 hcl:#ceb3a1 eyr:2021',\n",
       " 'byr:1999 hcl:#b6652a eyr:2023 hgt:175cm ecl:gry iyr:2013 cid:165 pid:194927609',\n",
       " 'hgt:70in eyr:2027 ecl:brn iyr:2012 pid:162238378 hcl:#ceb3a1 byr:1986',\n",
       " 'hgt:63in ecl:xry byr:2011 iyr:2024 hcl:5337b0',\n",
       " 'hcl:#341e13 eyr:2029 hgt:184cm ecl:amb iyr:2012 byr:1970',\n",
       " 'byr:1920 pid:472914751 eyr:2028 hgt:187cm hcl:#cfa07d cid:290 ecl:gry',\n",
       " 'byr:1948 ecl:gry eyr:2025 hgt:151cm cid:276 hcl:#6b5442 pid:937979267 iyr:2016',\n",
       " 'byr:1934 pid:626915978 hcl:#623a2f hgt:167cm ecl:gry iyr:2020 eyr:2023',\n",
       " 'byr:1949 hgt:68in eyr:2027 iyr:2019 hcl:#733820 ecl:brn cid:237 pid:057797826',\n",
       " 'pid:155cm hgt:68cm ecl:lzr hcl:z cid:344 eyr:2028 iyr:2020 byr:2017',\n",
       " 'byr:1959 hcl:#341e13 eyr:2022 iyr:2019 pid:728703569 hgt:167cm ecl:oth',\n",
       " 'ecl:grn eyr:2024 byr:1999 pid:566956828 iyr:2015 cid:293 hcl:#602927 hgt:192cm',\n",
       " 'byr:1939 ecl:xry pid:929512270 hgt:66in iyr:1939 eyr:2030 hcl:#efcc98',\n",
       " 'eyr:2026 iyr:2014 pid:176cm hcl:#fffffd ecl:gry hgt:151cm byr:1933 cid:256',\n",
       " 'ecl:oth eyr:2025 iyr:2017 hgt:159cm pid:055267863 cid:55 byr:2001 hcl:#cfa07d',\n",
       " 'eyr:2029 byr:1954 ecl:hzl cid:123 iyr:2020 hgt:192cm hcl:#866857 pid:225593536',\n",
       " 'pid:320274514 cid:289 byr:1963 eyr:1942 ecl:gmt hcl:z hgt:167in iyr:2022',\n",
       " 'byr:2013 ecl:gmt iyr:2011 hcl:#733820 pid:#e7962f hgt:178cm eyr:2029',\n",
       " 'pid:154cm ecl:hzl eyr:2035 byr:2023 cid:104 iyr:2026',\n",
       " 'eyr:2024 ecl:hzl hcl:#7d3b0c iyr:2010 pid:105864164 byr:1955 hgt:163cm',\n",
       " 'eyr:2021 hgt:151cm iyr:2017 hcl:#c0946f ecl:amb cid:150 pid:296798563 byr:1953',\n",
       " 'iyr:2012 byr:1990 hcl:#341e13 pid:189449931 eyr:2024 hgt:64in',\n",
       " 'hcl:z cid:79 byr:2028 eyr:2028 pid:886152432 ecl:#ce0596 hgt:178cm iyr:2029',\n",
       " 'ecl:brn iyr:2019 hgt:151cm hcl:#341e13 byr:1969 pid:468846056 eyr:2022',\n",
       " 'ecl:grn hgt:157cm iyr:2012 eyr:2020 hcl:#b6652a cid:338 byr:1954 pid:153867580',\n",
       " 'iyr:2011 eyr:2027 byr:1935 hgt:151cm ecl:blu pid:802665934 cid:276 hcl:#623a2f',\n",
       " 'hcl:#efcc98 eyr:2026 ecl:amb iyr:2014 pid:320160032 hgt:157cm byr:1976',\n",
       " 'eyr:2021 cid:172 iyr:2012 ecl:oth hgt:187cm pid:432856831 byr:2001 hcl:#733820',\n",
       " 'eyr:2028 ecl:amb hcl:#efcc98 iyr:2020 byr:1954 hgt:153cm',\n",
       " 'byr:1930 ecl:brn hcl:#fffffd pid:458840035 hgt:178cm eyr:2021 iyr:2011 cid:336',\n",
       " 'pid:216876576 hcl:#341e13 eyr:2028 iyr:2018 hgt:177cm byr:1938 ecl:brn cid:214',\n",
       " 'byr:2029 eyr:1987 hgt:75cm pid:193cm hcl:#b6652a cid:246 iyr:2028',\n",
       " 'ecl:hzl hgt:151cm hcl:#7d3b0c eyr:2030 pid:910999919 iyr:2019 byr:1956',\n",
       " 'byr:1950 cid:95 iyr:2013 ecl:grn eyr:2020 hcl:#623a2f pid:603817559 hgt:159cm',\n",
       " 'pid:913791667 iyr:2018 byr:1959 hcl:#a97842 hgt:179cm eyr:2029 ecl:gry',\n",
       " 'hgt:71in ecl:blu eyr:2028 hcl:#18171d byr:1937 iyr:2011 pid:951572571',\n",
       " 'hcl:#b6652a iyr:2015 hgt:170cm ecl:blu cid:292 byr:1977 pid:475457579 eyr:2020',\n",
       " 'ecl:amb eyr:2029 pid:530769382 iyr:2018 cid:53 hgt:63in byr:1954 hcl:#07de91',\n",
       " 'hcl:#cfa07d hgt:185cm byr:1929 iyr:2011 eyr:2027',\n",
       " 'iyr:2019 ecl:oth byr:2023 hcl:#341e13 pid:879919037 eyr:2030 hgt:174cm',\n",
       " 'hcl:z hgt:182cm ecl:grn iyr:2010 eyr:2020 pid:2063425865 cid:182 byr:2019',\n",
       " 'byr:1930 hgt:185cm pid:412694897 eyr:2025 ecl:brn iyr:2020 hcl:#a97842',\n",
       " 'hgt:150cm byr:1955 eyr:2020 cid:149 pid:597600808 hcl:#ceb3a1 ecl:hzl',\n",
       " 'pid:209568495 eyr:2026 byr:1928 hcl:#341e13 hgt:183cm ecl:brn iyr:2011',\n",
       " 'pid:723789670 ecl:blu iyr:2013 byr:1933 cid:239 hcl:#7d3b0c eyr:2026 hgt:151cm',\n",
       " 'byr:1978 eyr:2027 hgt:164cm pid:009071063 hcl:#602927 iyr:2014 ecl:blu',\n",
       " 'hcl:#18171d ecl:grn hgt:154cm cid:154 iyr:2016 byr:1952 pid:730027149 eyr:2024',\n",
       " 'eyr:2025 hcl:#888785 iyr:2013 cid:90 byr:1975 ecl:grn pid:619198428 hgt:161cm',\n",
       " 'ecl:gry iyr:2013 pid:795604673 cid:198 byr:1962 hcl:#6b5442 hgt:64in eyr:2021',\n",
       " 'hcl:#ceb3a1 ecl:oth iyr:2015 eyr:2021 pid:920586799 cid:302 hgt:60in byr:1964',\n",
       " 'eyr:2021 ecl:gry iyr:2019 hcl:#6b5442 hgt:192cm byr:1996 pid:692698177',\n",
       " 'ecl:grn pid:141369492 byr:1956 eyr:2028 hcl:#6b5442 hgt:190cm iyr:2014',\n",
       " 'hcl:#6b5442 ecl:grn iyr:2020 hgt:153cm pid:312738382 eyr:2028 byr:1985',\n",
       " 'byr:1979 eyr:2021 ecl:gry hgt:175cm pid:787676021 cid:81 hcl:#b6652a iyr:2012',\n",
       " 'cid:80 hgt:188cm byr:1964 pid:105773060 iyr:2014 hcl:#733820 ecl:gry eyr:2028',\n",
       " 'byr:1960 pid:251870522 iyr:2018 hgt:168cm ecl:blu hcl:#c0946f eyr:2026',\n",
       " 'cid:270 pid:#5661f0 hgt:182in ecl:dne byr:1930 hcl:z iyr:2026',\n",
       " 'hcl:#888785 byr:1954 pid:170544716 eyr:2028 hgt:162cm cid:244 iyr:2014 ecl:grn',\n",
       " 'iyr:2017 hgt:69in ecl:hzl pid:544135985 hcl:#ceb3a1 eyr:2020',\n",
       " 'hcl:92d4a1 iyr:2018 pid:178cm cid:347 hgt:97 eyr:2017 ecl:gmt byr:2004',\n",
       " 'ecl:oth iyr:2018 hcl:#fffffd byr:1999 pid:853396129 cid:119 eyr:2026 hgt:178cm',\n",
       " 'hgt:69in hcl:#fffffd eyr:2026 byr:1922 iyr:2010 ecl:oth pid:664840386',\n",
       " 'hgt:178cm byr:2000 iyr:2013 hcl:#cfa07d eyr:2028 pid:842454291 ecl:amb',\n",
       " 'ecl:hzl hcl:#733820 pid:316835287 byr:1998 eyr:2024 iyr:2015 hgt:165cm',\n",
       " 'pid:684064750 byr:1928 ecl:gry iyr:2015 cid:343 hgt:189cm hcl:#4c6cb4 eyr:2020',\n",
       " 'byr:1923 hcl:#a97842 eyr:2024 ecl:gry pid:095911913 hgt:185cm iyr:2010',\n",
       " 'ecl:hzl byr:1996 eyr:2023 hgt:177cm hcl:#b6652a pid:011541746 iyr:2011',\n",
       " 'hcl:#efcc98 iyr:2014 ecl:oth byr:1942 pid:730960830 hgt:183cm eyr:2025',\n",
       " 'byr:1939 eyr:2029 ecl:amb hcl:#fffffd hgt:188cm pid:732730418 iyr:2013 cid:313',\n",
       " 'hgt:164cm cid:217 byr:1985 hcl:#888785 eyr:2020 iyr:2014 ecl:oth pid:071172789',\n",
       " 'eyr:2024 pid:215897274 ecl:#c67898 byr:1972 hcl:#866857 iyr:2010 hgt:170cm cid:310',\n",
       " 'ecl:hzl pid:030118892 byr:1941 hgt:158cm hcl:#b6652a eyr:2029 iyr:2012',\n",
       " 'ecl:gry hcl:#c0946f hgt:166cm pid:604313781 byr:1924 eyr:2023 iyr:2020',\n",
       " 'hcl:#602927 hgt:168cm eyr:2027 ecl:brn pid:764635418 byr:1968 iyr:2010',\n",
       " 'pid:157933284 ecl:grn eyr:2030 byr:2000 hgt:81 hcl:z',\n",
       " 'hcl:#ec24d1 pid:647881680 byr:1922 hgt:178cm iyr:2020 ecl:amb eyr:2021 cid:94',\n",
       " 'ecl:hzl byr:1971 iyr:2018 pid:975690657 eyr:2027 hgt:192in cid:202 hcl:#c0946f',\n",
       " 'pid:678999378 hgt:61in byr:1981 hcl:#cfa07d eyr:2029 iyr:2014 ecl:oth',\n",
       " 'eyr:2022 iyr:2012 ecl:grn pid:883419125 hcl:#ceb3a1 cid:136 hgt:75in byr:1952',\n",
       " 'iyr:2018 hgt:185cm byr:1985 pid:119464380 eyr:2028 hcl:#623a2f ecl:gry',\n",
       " 'eyr:2025 hcl:#ceb3a1 byr:1953 cid:277 hgt:164cm iyr:2010 pid:574253234',\n",
       " 'cid:252 ecl:amb pid:594663323 hgt:75in hcl:#cfa07d iyr:2019 eyr:2026 byr:1964',\n",
       " 'iyr:2026 hcl:z pid:60117235 ecl:lzr byr:2016 hgt:156in eyr:1994',\n",
       " 'pid:448392350 eyr:2022 hcl:#a97842 hgt:157cm ecl:hzl iyr:2018 byr:1973',\n",
       " 'ecl:brn byr:1951 eyr:2028 hcl:#7d3b0c iyr:2018 hgt:164cm',\n",
       " 'hgt:156cm byr:1963 iyr:2014 eyr:2020 ecl:blu hcl:#ceb3a1 pid:#a87d16',\n",
       " 'pid:447170366 ecl:blu hcl:#888785 iyr:2012 cid:236 hgt:167cm eyr:2022 byr:1942',\n",
       " 'hcl:#623a2f eyr:2020 iyr:2017 cid:128 ecl:amb pid:279550425 byr:1983 hgt:154cm',\n",
       " 'byr:2014 eyr:2034 hgt:176in hcl:z ecl:#d4e521 pid:3629053477 cid:177 iyr:1970',\n",
       " 'pid:30370825 byr:1966 eyr:2026 iyr:2026 hcl:#866857 cid:346 ecl:#f7c189',\n",
       " 'iyr:2010 pid:271066119 eyr:2023 hcl:#efcc98 hgt:179cm byr:1956',\n",
       " 'byr:1966 hgt:156cm pid:977897485 cid:287 iyr:2011 hcl:#b6652a ecl:amb eyr:2029',\n",
       " 'cid:211 ecl:gmt byr:2017 hcl:z eyr:2029 hgt:180in iyr:2021 pid:81920053',\n",
       " 'byr:2019 pid:5229927737 hcl:75b4f1 hgt:146 iyr:2026 ecl:#92cf7d eyr:2032',\n",
       " 'eyr:2027 pid:604671573 ecl:hzl hgt:189cm byr:1979 hcl:#efcc98 iyr:2020',\n",
       " 'iyr:2018 cid:192 eyr:2029 ecl:grn pid:653764645 hgt:179cm hcl:#341e13 byr:1927',\n",
       " 'byr:2012 iyr:2015 hcl:#b6652a pid:168500059 eyr:2038 cid:234 hgt:191cm ecl:zzz',\n",
       " 'ecl:gry hcl:#623a2f byr:1925 iyr:2016 eyr:2028 cid:157 hgt:154cm pid:196280865',\n",
       " 'cid:319 pid:928322396 ecl:gry byr:1949 eyr:2028 hcl:#341e13 hgt:171cm iyr:2018',\n",
       " 'byr:2023 iyr:1953 hgt:154cm ecl:dne hcl:#888785 pid:066246061 eyr:1983',\n",
       " 'hcl:z iyr:2016 byr:1986 ecl:utc hgt:179cm eyr:2019 pid:583251408',\n",
       " 'ecl:amb iyr:2014 pid:499004360 byr:1927 eyr:2021 hgt:193cm hcl:#ceb3a1',\n",
       " 'pid:631303194 ecl:gry hcl:#18171d cid:216 iyr:2019 eyr:2024 hgt:178cm',\n",
       " 'hcl:#341e13 cid:201 byr:1949 iyr:2019 ecl:gry pid:372356205 eyr:2024',\n",
       " 'hcl:#18171d pid:867489359 hgt:185cm iyr:2020 ecl:amb eyr:2030 byr:1955',\n",
       " 'byr:1991 ecl:brn eyr:2025 hgt:184cm iyr:2016 pid:202216365',\n",
       " 'ecl:xry pid:#524139 hgt:151cm hcl:z eyr:2031 byr:2030 iyr:2005',\n",
       " 'byr:1971 hgt:178cm ecl:amb hcl:#ceb3a1 iyr:2010 eyr:2026 pid:396974525',\n",
       " 'iyr:2014 hgt:177cm pid:928522073 eyr:2022 ecl:hzl hcl:#c0946f byr:1983',\n",
       " 'hgt:167cm hcl:#ceb3a1 iyr:2014 pid:172415447 eyr:2020 byr:1956',\n",
       " 'iyr:2011 hgt:188cm byr:1947 eyr:2020 pid:667108134 ecl:amb hcl:#44a86b',\n",
       " 'cid:302 ecl:brn pid:292483175 hgt:154cm byr:1997 eyr:2026 iyr:2014 hcl:#623a2f',\n",
       " 'hgt:171cm iyr:2014 hcl:z ecl:hzl pid:321513523 eyr:2027 cid:146 byr:2001',\n",
       " 'eyr:1956 ecl:dne hgt:75cm hcl:82e1fa iyr:2030 byr:2027',\n",
       " 'eyr:2020 iyr:2011 pid:656669479 ecl:oth hgt:151cm hcl:#efcc98 byr:1981',\n",
       " 'iyr:2013 byr:1934 pid:142890410 hgt:62in eyr:2022 hcl:#87cca4 ecl:hzl',\n",
       " 'pid:006232726 hgt:173cm ecl:hzl cid:110 eyr:2026 hcl:#866857 iyr:2017 byr:1992',\n",
       " 'cid:208 iyr:2014 ecl:brn eyr:2024 byr:1935 hgt:187cm hcl:#b6652a pid:770836724',\n",
       " 'iyr:2014 cid:144 hgt:169cm eyr:2022 ecl:oth pid:117575716 hcl:#fffffd byr:1926',\n",
       " 'byr:1971 ecl:brn hcl:#733820 eyr:1942 iyr:2013 pid:606274259 hgt:163cm cid:196',\n",
       " 'byr:1964 pid:997828217 eyr:2029 iyr:2017 ecl:blu hcl:#341e13 hgt:158cm',\n",
       " 'pid:568202531 hcl:#efcc98 hgt:154cm eyr:2029 iyr:2010 byr:1946 ecl:blu',\n",
       " 'iyr:2011 pid:619355919 byr:1955 ecl:brn hcl:#888785 eyr:2030 hgt:155cm',\n",
       " 'ecl:hzl pid:367152545 hgt:162cm cid:221 hcl:#866857 eyr:2024 byr:1997 iyr:2019',\n",
       " 'hgt:157in cid:268 hcl:32371d byr:2020 ecl:zzz pid:1081234390',\n",
       " 'ecl:hzl eyr:2026 byr:1969 pid:850482906 cid:166 hcl:#602927 hgt:60in iyr:2019',\n",
       " 'hcl:#c0946f hgt:176cm ecl:brn eyr:2026 iyr:2018 cid:172 byr:1986 pid:172963254',\n",
       " 'ecl:grn iyr:2016 hgt:187cm byr:1983 hcl:#efcc98 pid:722084344 eyr:2025',\n",
       " 'ecl:oth hcl:#341e13 pid:130312766 hgt:171cm iyr:2018 byr:1927 eyr:2024',\n",
       " 'byr:2021 hgt:152cm hcl:74dda6 eyr:1984 cid:216 iyr:2018 pid:95283942',\n",
       " 'hcl:#b6652a pid:924778815 iyr:2017 ecl:gry eyr:2035 hgt:68cm',\n",
       " 'iyr:2010 hcl:#efcc98 ecl:brn eyr:2020 pid:801894599 hgt:163cm byr:1959',\n",
       " 'pid:798701070 eyr:2030 hcl:#866857 ecl:hzl hgt:169cm byr:1994 cid:219 iyr:2010',\n",
       " 'pid:#e9b41b hcl:#341e13 byr:1970 iyr:2014 ecl:oth cid:266 hgt:68cm eyr:2023',\n",
       " 'byr:1931 pid:929960843 hgt:187cm hcl:#6b5442 cid:52 iyr:2010 eyr:2024 ecl:brn',\n",
       " 'iyr:2017 byr:1974 ecl:hzl cid:243 pid:66053995 hgt:147 eyr:1920 hcl:z',\n",
       " 'iyr:2012 byr:1962 ecl:brn pid:773399437 hcl:#341e13 eyr:2026',\n",
       " 'pid:738442771 hgt:186cm eyr:2027 hcl:#efcc98 iyr:2013 ecl:brn byr:1928',\n",
       " 'pid:855794198 ecl:oth hgt:67in cid:81 iyr:2011 hcl:#b6652a eyr:2020 byr:1921',\n",
       " 'hcl:176abf hgt:161in byr:2002 iyr:2016 eyr:2027 pid:639047770 ecl:brn cid:178',\n",
       " 'pid:335686451 hcl:#86c240 iyr:2017 hgt:190cm byr:1968 ecl:amb',\n",
       " 'hgt:150cm hcl:094a87 ecl:#09c463 eyr:1926 pid:537511570 byr:2009 iyr:1998',\n",
       " 'hgt:74in pid:927963411 eyr:2026 ecl:gry cid:323 iyr:2012 hcl:#fffffd byr:1959',\n",
       " 'iyr:2018 byr:1978 hcl:#ff1829 eyr:2023 pid:823129853 ecl:hzl hgt:65in',\n",
       " 'pid:189cm ecl:#00391e hgt:72cm hcl:11050f byr:2029 eyr:1994 iyr:1935 cid:186',\n",
       " 'ecl:grn byr:1942 pid:217290710 hgt:181cm eyr:2021 hcl:#7d3b0c iyr:2019 cid:320',\n",
       " 'byr:1983 iyr:2013 cid:122 hcl:#ceb3a1 eyr:2030 hgt:59in ecl:grn pid:946451564',\n",
       " 'ecl:amb cid:236 hgt:184cm hcl:#cfa07d iyr:2017 pid:934730535 eyr:2021 byr:2002',\n",
       " 'byr:1950 ecl:hzl eyr:2030 hcl:#623a2f pid:742249321 hgt:158cm iyr:2018',\n",
       " 'byr:1946 eyr:2021 hcl:#a97842 pid:204671558 ecl:grn iyr:2010 hgt:187cm',\n",
       " 'hcl:#b6652a pid:528124882 hgt:162cm byr:1924 ecl:amb iyr:2027 cid:157 eyr:2028',\n",
       " 'hgt:180cm iyr:2013 byr:1926 pid:232265934 hcl:#602927 ecl:oth',\n",
       " 'byr:1984 ecl:brn iyr:2016 pid:756596443 eyr:2030 hcl:#7d3b0c hgt:183cm',\n",
       " 'hgt:185cm hcl:#fffffd byr:1991 eyr:2023 iyr:2014 ecl:amb pid:759105859',\n",
       " 'cid:82 iyr:2012 hgt:160cm eyr:2022 pid:593798464 ecl:gry hcl:#4e7571 byr:1983',\n",
       " 'pid:478427550 iyr:2010 ecl:amb byr:1969 hgt:68in cid:94 eyr:2021 hcl:#866857',\n",
       " 'ecl:amb iyr:2019 byr:1986 hgt:170cm hcl:#c0946f pid:779205106 eyr:2027',\n",
       " 'ecl:brn eyr:2025 byr:1925 hcl:#7d3b0c hgt:76in pid:576353079 iyr:2010',\n",
       " 'hgt:175cm hcl:4bf5ae ecl:amb eyr:2029 pid:173cm cid:329 iyr:1952 byr:1972',\n",
       " 'ecl:grn eyr:2030 iyr:2015 hcl:#c0946f byr:1989 hgt:178cm pid:287209519',\n",
       " 'pid:834505198 byr:1985 ecl:gry eyr:2024 cid:295 hgt:169cm iyr:2017',\n",
       " 'hgt:170cm pid:054644831 eyr:2023 iyr:1949 ecl:amb hcl:#888785 byr:1955',\n",
       " 'hgt:171cm pid:947263309 iyr:2015 byr:1944 eyr:2027 ecl:grn cid:79 hcl:#341e13',\n",
       " 'eyr:1982 cid:147 iyr:2015 hgt:70cm hcl:a77c10 ecl:zzz byr:2007 pid:161cm',\n",
       " 'ecl:gry byr:1933 hcl:#c0946f pid:483275512 iyr:2012 eyr:2025 hgt:161cm',\n",
       " 'eyr:1985 hgt:176cm hcl:7b6ddc iyr:2012 cid:326 byr:1973 pid:929418396 ecl:gmt',\n",
       " 'ecl:gry byr:1971 hgt:184cm eyr:2027 hcl:#3adf2c iyr:2017 cid:210 pid:693561862',\n",
       " 'eyr:2021 pid:779298835 byr:1921 hgt:193cm ecl:amb iyr:2016 hcl:#ceb3a1',\n",
       " 'hcl:4a1444 byr:2019 iyr:2024 hgt:182in cid:87 ecl:#122264 pid:181cm eyr:1927',\n",
       " 'cid:267 ecl:amb eyr:2020 byr:2000 hcl:#18171d iyr:2012 hgt:190cm pid:18525759',\n",
       " 'ecl:oth byr:1988 iyr:2019 pid:660570833 hcl:#866857 hgt:176cm',\n",
       " 'eyr:2030 hcl:#866857 byr:1967 cid:316 pid:560346474 iyr:2015 hgt:160cm ecl:gry',\n",
       " 'ecl:hzl iyr:2014 hgt:164cm hcl:#733820 eyr:2025 pid:106302413 byr:1920',\n",
       " 'iyr:2016 pid:515066491 ecl:grn eyr:2026 hgt:179cm hcl:#b6652a byr:1982',\n",
       " 'ecl:#7de6a0 iyr:2004 eyr:1955 hgt:154cm cid:138 byr:2004 pid:758934555 hcl:a21980',\n",
       " 'pid:#2a21e0 ecl:#1b9b27 hgt:165in byr:1998 iyr:2014 eyr:2032',\n",
       " 'eyr:2021 hgt:184cm pid:431054313 hcl:#ceb3a1 cid:109 byr:1977 ecl:blu iyr:2011',\n",
       " 'pid:006339126 hgt:177cm cid:188 hcl:#a97842 iyr:1959 ecl:xry',\n",
       " 'byr:2000 ecl:hzl eyr:2029 iyr:2011 hcl:#866857 hgt:74in']"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.DataFrame(columns=['byr','iyr','eyr', 'hgt', 'hcl', 'ecl', 'pid','cid'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "for passport in raw : \n",
    "    passport = passport.split(' ')\n",
    "    dic = {}\n",
    "    for info in passport : \n",
    "        #print(info,info.split(':'))\n",
    "        dic[info.split(':')[0]] = info.split(':')[1]\n",
    "    data = data.append(dic,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(290, 7)\n"
     ]
    }
   ],
   "source": [
    "data.drop('cid', axis = 1, inplace = True)\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.dropna(axis=0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is a total of 237 valid passport for part 1\n"
     ]
    }
   ],
   "source": [
    "print('There is a total of {} valid passport for part 1'.format(data.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>byr</th>\n",
       "      <th>iyr</th>\n",
       "      <th>eyr</th>\n",
       "      <th>hgt</th>\n",
       "      <th>hcl</th>\n",
       "      <th>ecl</th>\n",
       "      <th>pid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>97</td>\n",
       "      <td>32</td>\n",
       "      <td>37</td>\n",
       "      <td>84</td>\n",
       "      <td>52</td>\n",
       "      <td>28</td>\n",
       "      <td>236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>1955</td>\n",
       "      <td>2014</td>\n",
       "      <td>2026</td>\n",
       "      <td>151cm</td>\n",
       "      <td>z</td>\n",
       "      <td>grn</td>\n",
       "      <td>155cm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>25</td>\n",
       "      <td>13</td>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         byr   iyr   eyr    hgt  hcl  ecl    pid\n",
       "count    237   237   237    237  237  237    237\n",
       "unique    97    32    37     84   52   28    236\n",
       "top     1955  2014  2026  151cm    z  grn  155cm\n",
       "freq       6    31    25     13   19   34      2"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(237, 7) \n",
      " byr    object\n",
      "iyr    object\n",
      "eyr    object\n",
      "hgt    object\n",
      "hcl    object\n",
      "ecl    object\n",
      "pid    object\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data.shape,'\\n' ,data.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['byr'] = data['byr'].astype(int)\n",
    "data['iyr'] = data['iyr'].astype(int)\n",
    "data['eyr'] = data['eyr'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>byr</th>\n",
       "      <th>iyr</th>\n",
       "      <th>eyr</th>\n",
       "      <th>hgt</th>\n",
       "      <th>hcl</th>\n",
       "      <th>ecl</th>\n",
       "      <th>pid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1926</td>\n",
       "      <td>2010</td>\n",
       "      <td>2021</td>\n",
       "      <td>186cm</td>\n",
       "      <td>#7d3b0c</td>\n",
       "      <td>hzl</td>\n",
       "      <td>221225902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1926</td>\n",
       "      <td>2010</td>\n",
       "      <td>2020</td>\n",
       "      <td>178</td>\n",
       "      <td>#efcc98</td>\n",
       "      <td>blu</td>\n",
       "      <td>433543520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1946</td>\n",
       "      <td>2018</td>\n",
       "      <td>2026</td>\n",
       "      <td>158cm</td>\n",
       "      <td>#b6652a</td>\n",
       "      <td>brn</td>\n",
       "      <td>822320101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>2010</td>\n",
       "      <td>1937</td>\n",
       "      <td>138</td>\n",
       "      <td>z</td>\n",
       "      <td>grn</td>\n",
       "      <td>21019503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>2019</td>\n",
       "      <td>1990</td>\n",
       "      <td>176in</td>\n",
       "      <td>z</td>\n",
       "      <td>#d06796</td>\n",
       "      <td>153cm</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    byr   iyr   eyr    hgt      hcl      ecl        pid\n",
       "0  1926  2010  2021  186cm  #7d3b0c      hzl  221225902\n",
       "1  1926  2010  2020    178  #efcc98      blu  433543520\n",
       "2  1946  2018  2026  158cm  #b6652a      brn  822320101\n",
       "3  2008  2010  1937    138        z      grn   21019503\n",
       "4  2018  2019  1990  176in        z  #d06796      153cm"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Putting one filter per condition\n",
    "data = data[ 1920 <= data['byr'] ]\n",
    "data = data[ data['byr'] <= 2002 ]\n",
    "\n",
    "data = data[ 2010 <= data['iyr'] ]\n",
    "data = data[ data['iyr'] <= 2020 ]\n",
    "\n",
    "data = data[ 2020 <= data['eyr'] ]\n",
    "data = data[ data['eyr'] <= 2030 ]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For the other characteristics, must do differently\n",
    "valid_ecl = ['amb', 'blu', 'brn', 'gry', 'grn', 'hzl', 'oth']\n",
    "\n",
    "for ind in data.index : \n",
    "    to_drop = False\n",
    "    # Looking for invalid height\n",
    "    if data['hgt'][ind][-2:]=='cm':\n",
    "        if (150 <= int(data['hgt'][ind][:-2]) ) and ( int(data['hgt'][ind][:-2]) <= 193) :\n",
    "            pass\n",
    "        else : \n",
    "            to_drop = True\n",
    "    elif data['hgt'][ind][-2:]=='in':\n",
    "        if (59 <= int(data['hgt'][ind][:-2]) ) and ( int(data['hgt'][ind][:-2]) <= 76) :\n",
    "            pass\n",
    "        else : \n",
    "            to_drop = True\n",
    "    else :\n",
    "        to_drop = True\n",
    "        \n",
    "        \n",
    "    # Looking for invalid hair color \n",
    "    if (data['hcl'][ind][0]=='#' and len(re.findall('[0-9A-Fa-f]',data['hcl'][ind] )) == 6) :\n",
    "        pass\n",
    "    else : \n",
    "        to_drop = True\n",
    "        \n",
    "    # Looking for invalid eye color \n",
    "    if data['ecl'][ind] in valid_ecl : \n",
    "        pass\n",
    "    else : \n",
    "        to_drop = True\n",
    "    \n",
    "    # Looking for invalid pid \n",
    "    if len(re.findall('[0-9A-Fa-f]', data['pid'][ind] )) == 9 :\n",
    "        pass\n",
    "    else :\n",
    "        to_drop = True\n",
    "        \n",
    "    if to_drop : data.drop(ind, axis = 0, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of valid passport after part 2 is 172\n"
     ]
    }
   ],
   "source": [
    "print('The number of valid passport after part 2 is', data.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oui\n"
     ]
    }
   ],
   "source": [
    "ind = 0\n",
    "if len(re.findall('[0-9A-Fa-f]', data['pid'][ind] )) == 9 :\n",
    "    print('oui')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(re.findall('[0-9A-Fa-f]', 'aas30d@sa20'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = root_dir+'inputs/input_5.txt'\n",
    "\n",
    "if os.path.exists(file_path):\n",
    "    data = pd.read_csv(file_path,sep = '\\n', header = None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.columns = ['spec']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "def row_to_binary(raw_row):\n",
    "    bin_row = re.sub('F','0',raw_row)\n",
    "    bin_row = re.sub('B','1',bin_row)\n",
    "    \n",
    "    return bin_row\n",
    "\n",
    "def col_to_binary(raw_col):\n",
    "    bin_col = re.sub('R','1',raw_col)\n",
    "    bin_col = re.sub('L','0',bin_col)\n",
    "    return bin_col\n",
    "\n",
    "def bin_to_num(binary):\n",
    "    summ = 0\n",
    "    binary = binary[::-1]\n",
    "    for i in range(len(binary)) : \n",
    "        summ += int(binary[i])*2**i\n",
    "    return summ\n",
    "\n",
    "def convert_spec(spec):\n",
    "    raw_row = spec[:7]\n",
    "    raw_col = spec[7:]\n",
    "    \n",
    "    bin_row = row_to_binary(raw_row)\n",
    "    bin_col = col_to_binary(raw_col)\n",
    "    \n",
    "    row = bin_to_num(bin_row)\n",
    "    col = bin_to_num(bin_col)\n",
    "    #print('raw:',raw_row,raw_col)\n",
    "    #print('bin:',bin_row,bin_col)\n",
    "    #print('num:',row,col)\n",
    "    return row,col\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = []\n",
    "rows = []\n",
    "for raw in data['spec']:\n",
    "    conv = convert_spec(raw)\n",
    "    rows.append(conv[0])\n",
    "    cols.append(conv[1])\n",
    "data['row'] = rows\n",
    "data['col'] = cols\n",
    "data['seatID'] = 8*data['row']+data['col']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>spec</th>\n",
       "      <th>row</th>\n",
       "      <th>col</th>\n",
       "      <th>seatID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FFBBBFFLRL</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BFFBFBFRLR</td>\n",
       "      <td>74</td>\n",
       "      <td>5</td>\n",
       "      <td>597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FFFBBFBRRR</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BFFBBBBRRL</td>\n",
       "      <td>79</td>\n",
       "      <td>6</td>\n",
       "      <td>638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FFFBBFBLLR</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>BFFFBBFLLR</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877</th>\n",
       "      <td>FFFBFBFRLL</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>FFFBBBBRRR</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>FBFBBBFRRL</td>\n",
       "      <td>46</td>\n",
       "      <td>6</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>BFFFBBBRLR</td>\n",
       "      <td>71</td>\n",
       "      <td>5</td>\n",
       "      <td>573</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>881 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           spec  row  col  seatID\n",
       "0    FFBBBFFLRL   28    2     226\n",
       "1    BFFBFBFRLR   74    5     597\n",
       "2    FFFBBFBRRR   13    7     111\n",
       "3    BFFBBBBRRL   79    6     638\n",
       "4    FFFBBFBLLR   13    1     105\n",
       "..          ...  ...  ...     ...\n",
       "876  BFFFBBFLLR   70    1     561\n",
       "877  FFFBFBFRLL   10    4      84\n",
       "878  FFFBBBBRRR   15    7     127\n",
       "879  FBFBBBFRRL   46    6     374\n",
       "880  BFFFBBBRLR   71    5     573\n",
       "\n",
       "[881 rows x 4 columns]"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>row</th>\n",
       "      <th>col</th>\n",
       "      <th>seatID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>881.000000</td>\n",
       "      <td>881.000000</td>\n",
       "      <td>881.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>58.591373</td>\n",
       "      <td>3.491487</td>\n",
       "      <td>472.222474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>31.846273</td>\n",
       "      <td>2.295298</td>\n",
       "      <td>254.767033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>32.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>252.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>59.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>472.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>86.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>692.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>114.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>913.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              row         col      seatID\n",
       "count  881.000000  881.000000  881.000000\n",
       "mean    58.591373    3.491487  472.222474\n",
       "std     31.846273    2.295298  254.767033\n",
       "min      4.000000    0.000000   32.000000\n",
       "25%     31.000000    1.000000  252.000000\n",
       "50%     59.000000    3.000000  472.000000\n",
       "75%     86.000000    5.000000  692.000000\n",
       "max    114.000000    7.000000  913.000000"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On the list, the max seat ID is 913\n"
     ]
    }
   ],
   "source": [
    "print('On the list, the max seat ID is',np.max(data['seatID']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The only seat left is  717\n"
     ]
    }
   ],
   "source": [
    "sorted_ID = np.sort(data['seatID'])\n",
    "for ind in range(1,len(sorted_ID)-1):\n",
    "    if not(sorted_ID[ind]-1 == sorted_ID[ind-1]):\n",
    "        print('The only seat left is ',sorted_ID[ind]-1)\n",
    "                    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = root_dir+'inputs/input_6.txt'\n",
    "\n",
    "if os.path.exists(file_path):\n",
    "    file = open(file_path,'r')\n",
    "    \n",
    "raw = file.read()\n",
    "raw = raw[:-1]\n",
    "\n",
    "#raw='abc\\n\\na\\nb\\nc\\n\\nab\\nac\\n\\na\\na\\na\\na\\n\\nb'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups = raw.split('\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "500"
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(groups)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For part 1, the sum is : 6742\n"
     ]
    }
   ],
   "source": [
    "summ = 0\n",
    "for group in groups : \n",
    "    group = re.sub('\\n','',group)\n",
    "    group = [g for g in group]\n",
    "    group = np.unique(group)\n",
    "    \n",
    "    summ += len(group)\n",
    "print('For part 1, the sum is :',summ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For part 2, the sum is : 3447\n"
     ]
    }
   ],
   "source": [
    "summ = 0\n",
    "for group in groups : \n",
    "    nb_in_gp = len(group.split('\\n'))\n",
    "    group = re.sub('\\n','',group)\n",
    "    group = [g for g in group]\n",
    "    uniq, count = np.unique(group, return_counts = True)\n",
    "    filtre = count==nb_in_gp\n",
    "    summ += np.sum(filtre)\n",
    "    #print(group, nb_in_gp, count,filtre,np.sum(filtre))\n",
    "print('For part 2, the sum is :',summ)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day 7 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 810,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = root_dir+'inputs/input_7.txt'\n",
    "#file_path = root_dir+'inputs/example_input_7.txt'\n",
    "\n",
    "if os.path.exists(file_path):\n",
    "    file = open(file_path,'r')\n",
    "    \n",
    "raw = file.read()\n",
    "raw = raw[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 811,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "594\n"
     ]
    }
   ],
   "source": [
    "rules = raw.split('\\n')\n",
    "print(len(rules))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 812,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['vibrant salmon bags contain 1 vibrant gold bag, 2 wavy aqua bags, 1 dotted crimson bag.',\n",
       " 'dotted plum bags contain 3 wavy cyan bags.',\n",
       " 'muted salmon bags contain 2 pale purple bags, 3 dull orange bags, 2 dotted lime bags, 3 clear crimson bags.',\n",
       " 'wavy green bags contain 1 plaid crimson bag.',\n",
       " 'light salmon bags contain 3 posh lime bags, 1 plaid plum bag, 3 faded yellow bags, 4 clear fuchsia bags.',\n",
       " 'dim violet bags contain 4 drab tan bags, 4 drab violet bags, 2 faded coral bags, 4 dark white bags.',\n",
       " 'dim black bags contain 4 posh lime bags.',\n",
       " 'drab indigo bags contain 4 light aqua bags, 2 light white bags, 4 clear plum bags.',\n",
       " 'clear purple bags contain 4 drab olive bags, 2 vibrant chartreuse bags.',\n",
       " 'wavy indigo bags contain 3 clear maroon bags, 4 striped blue bags, 2 wavy gray bags, 2 dim magenta bags.',\n",
       " 'drab olive bags contain 2 shiny salmon bags, 4 mirrored white bags, 4 mirrored fuchsia bags.',\n",
       " 'plaid crimson bags contain 2 dull chartreuse bags, 4 striped maroon bags, 4 dull crimson bags, 4 plaid red bags.',\n",
       " 'pale lavender bags contain 4 dotted tan bags, 5 striped olive bags.',\n",
       " 'vibrant maroon bags contain 2 faded plum bags, 4 wavy aqua bags, 5 drab lavender bags, 4 light lavender bags.',\n",
       " 'wavy coral bags contain 5 drab purple bags.',\n",
       " 'drab salmon bags contain 4 shiny tan bags, 2 shiny white bags.',\n",
       " 'light green bags contain 5 dim turquoise bags, 4 striped crimson bags, 5 dim salmon bags, 3 clear gray bags.',\n",
       " 'dark indigo bags contain 5 shiny crimson bags.',\n",
       " 'dark blue bags contain 3 drab indigo bags, 2 shiny beige bags, 2 shiny coral bags.',\n",
       " 'shiny cyan bags contain 2 striped aqua bags, 2 drab turquoise bags, 5 light purple bags.',\n",
       " 'pale cyan bags contain 2 muted violet bags, 2 clear beige bags, 1 clear indigo bag, 5 striped turquoise bags.',\n",
       " 'muted lime bags contain 5 drab silver bags.',\n",
       " 'shiny brown bags contain 4 clear purple bags, 5 striped chartreuse bags, 5 pale lavender bags.',\n",
       " 'muted purple bags contain 4 dark purple bags, 2 dull crimson bags.',\n",
       " 'plaid turquoise bags contain 2 clear gray bags, 4 clear magenta bags, 4 dull bronze bags.',\n",
       " 'clear cyan bags contain 3 dotted plum bags, 3 shiny coral bags.',\n",
       " 'shiny violet bags contain 3 drab chartreuse bags, 1 pale aqua bag, 3 bright aqua bags.',\n",
       " 'wavy tan bags contain 5 dark magenta bags, 4 dull beige bags, 1 wavy cyan bag.',\n",
       " 'mirrored lime bags contain 2 clear plum bags, 3 dark bronze bags, 5 faded turquoise bags, 5 plaid crimson bags.',\n",
       " 'wavy purple bags contain 3 dark bronze bags, 2 bright bronze bags.',\n",
       " 'plaid plum bags contain 5 muted tan bags, 1 drab teal bag, 2 dark purple bags, 1 dotted blue bag.',\n",
       " 'dotted cyan bags contain 4 vibrant fuchsia bags, 3 muted plum bags.',\n",
       " 'striped white bags contain 3 faded salmon bags, 4 plaid cyan bags, 5 wavy gray bags.',\n",
       " 'posh black bags contain 2 dotted blue bags, 3 muted crimson bags.',\n",
       " 'dotted bronze bags contain 2 posh tan bags.',\n",
       " 'muted gray bags contain 2 posh green bags.',\n",
       " 'plaid violet bags contain 4 muted orange bags.',\n",
       " 'muted green bags contain 3 drab silver bags, 2 mirrored maroon bags, 3 dark teal bags.',\n",
       " 'dotted tan bags contain 3 pale black bags.',\n",
       " 'dim beige bags contain 4 light plum bags, 4 posh blue bags, 4 dotted purple bags.',\n",
       " 'posh magenta bags contain 2 clear purple bags, 4 posh aqua bags.',\n",
       " 'bright coral bags contain 5 light bronze bags, 2 vibrant crimson bags, 4 dark gold bags.',\n",
       " 'pale bronze bags contain 1 striped orange bag.',\n",
       " 'dim lime bags contain 3 dim green bags.',\n",
       " 'plaid green bags contain 2 faded brown bags, 3 faded bronze bags, 3 pale green bags, 5 plaid magenta bags.',\n",
       " 'vibrant cyan bags contain 5 pale black bags, 5 vibrant violet bags, 1 mirrored red bag.',\n",
       " 'dotted fuchsia bags contain 3 dull crimson bags, 2 wavy silver bags, 4 muted purple bags.',\n",
       " 'dim red bags contain 2 clear indigo bags, 5 dotted yellow bags.',\n",
       " 'faded black bags contain 4 bright fuchsia bags.',\n",
       " 'faded chartreuse bags contain 4 striped orange bags.',\n",
       " 'plaid blue bags contain 5 dim gray bags, 2 pale salmon bags, 2 muted orange bags.',\n",
       " 'plaid teal bags contain 5 bright lavender bags.',\n",
       " 'drab magenta bags contain 2 dim crimson bags, 1 bright fuchsia bag.',\n",
       " 'clear violet bags contain 3 mirrored white bags, 5 faded lime bags, 2 light olive bags, 1 dotted turquoise bag.',\n",
       " 'posh tan bags contain 3 posh orange bags, 1 vibrant purple bag, 4 posh gray bags, 2 mirrored fuchsia bags.',\n",
       " 'posh red bags contain 5 mirrored red bags.',\n",
       " 'striped lavender bags contain 5 dotted crimson bags, 1 dotted purple bag.',\n",
       " 'dull salmon bags contain 1 wavy black bag, 2 dull lime bags, 3 bright plum bags, 2 dark gray bags.',\n",
       " 'light tan bags contain 3 wavy violet bags, 1 shiny olive bag, 5 bright brown bags.',\n",
       " 'pale orange bags contain 5 vibrant orange bags, 3 wavy black bags.',\n",
       " 'mirrored green bags contain 1 dark tan bag.',\n",
       " 'plaid gray bags contain 4 muted magenta bags.',\n",
       " 'dim maroon bags contain 3 light magenta bags, 4 dull red bags.',\n",
       " 'dull cyan bags contain 1 wavy blue bag, 1 dark chartreuse bag.',\n",
       " 'mirrored blue bags contain 4 dark cyan bags, 4 muted magenta bags, 2 striped olive bags, 1 posh gold bag.',\n",
       " 'plaid purple bags contain 1 shiny orange bag, 5 plaid coral bags, 4 dim red bags, 5 faded aqua bags.',\n",
       " 'vibrant magenta bags contain 5 posh aqua bags, 5 shiny chartreuse bags, 4 dark teal bags.',\n",
       " 'bright indigo bags contain 1 dark bronze bag.',\n",
       " 'bright yellow bags contain 4 muted lime bags, 1 drab maroon bag.',\n",
       " 'clear gold bags contain 2 striped blue bags, 3 clear green bags, 4 drab indigo bags.',\n",
       " 'wavy red bags contain 5 faded fuchsia bags, 5 mirrored indigo bags.',\n",
       " 'dark coral bags contain 3 drab aqua bags, 5 bright fuchsia bags.',\n",
       " 'striped teal bags contain 1 clear red bag, 3 drab magenta bags, 4 dim green bags, 2 dark fuchsia bags.',\n",
       " 'pale salmon bags contain 1 muted gray bag, 4 dotted lavender bags, 3 dark maroon bags, 4 plaid plum bags.',\n",
       " 'dull plum bags contain 3 dim black bags, 5 shiny aqua bags, 3 pale teal bags, 4 clear purple bags.',\n",
       " 'plaid indigo bags contain 4 drab maroon bags, 2 shiny chartreuse bags, 4 shiny yellow bags, 1 pale violet bag.',\n",
       " 'shiny orange bags contain 5 bright silver bags, 2 light olive bags, 5 light beige bags.',\n",
       " 'dotted salmon bags contain 4 posh chartreuse bags, 4 light crimson bags, 5 muted yellow bags.',\n",
       " 'vibrant aqua bags contain 2 dull brown bags.',\n",
       " 'shiny bronze bags contain 1 mirrored teal bag, 2 drab tomato bags.',\n",
       " 'dark black bags contain 5 muted red bags, 5 mirrored crimson bags.',\n",
       " 'muted bronze bags contain 3 clear tomato bags, 1 vibrant purple bag.',\n",
       " 'faded beige bags contain 1 shiny blue bag, 5 plaid lime bags.',\n",
       " 'pale green bags contain 2 pale crimson bags, 4 muted cyan bags.',\n",
       " 'vibrant bronze bags contain 1 bright lavender bag.',\n",
       " 'posh salmon bags contain 1 clear green bag, 2 plaid yellow bags, 3 bright orange bags.',\n",
       " 'dull yellow bags contain 1 clear plum bag, 2 dim bronze bags.',\n",
       " 'mirrored indigo bags contain 5 dark tomato bags, 5 pale coral bags, 5 light magenta bags, 5 striped turquoise bags.',\n",
       " 'muted chartreuse bags contain 3 dark tan bags, 4 dotted teal bags.',\n",
       " 'drab bronze bags contain 3 pale lavender bags, 1 bright salmon bag, 4 plaid red bags.',\n",
       " 'dim cyan bags contain 1 bright plum bag.',\n",
       " 'drab purple bags contain 1 dim fuchsia bag, 4 mirrored turquoise bags, 5 striped blue bags.',\n",
       " 'pale violet bags contain 5 posh brown bags, 5 striped plum bags, 1 dotted indigo bag.',\n",
       " 'wavy maroon bags contain 3 shiny blue bags, 3 wavy cyan bags, 1 faded purple bag, 4 posh lime bags.',\n",
       " 'vibrant coral bags contain 3 shiny turquoise bags, 4 mirrored maroon bags.',\n",
       " 'vibrant lavender bags contain 2 drab turquoise bags, 2 clear red bags.',\n",
       " 'striped fuchsia bags contain 4 dotted tan bags, 4 posh silver bags, 4 clear maroon bags, 5 wavy fuchsia bags.',\n",
       " 'muted lavender bags contain 2 pale aqua bags, 2 bright green bags, 5 posh beige bags.',\n",
       " 'posh tomato bags contain 2 vibrant bronze bags, 3 light brown bags, 5 posh indigo bags.',\n",
       " 'dull lavender bags contain 2 wavy olive bags.',\n",
       " 'mirrored violet bags contain 5 wavy violet bags, 2 posh cyan bags, 2 dull olive bags, 3 drab yellow bags.',\n",
       " 'mirrored chartreuse bags contain 2 shiny salmon bags, 5 dark purple bags, 2 posh lime bags.',\n",
       " 'dim brown bags contain 4 clear red bags, 1 drab blue bag, 1 pale silver bag, 5 dark gray bags.',\n",
       " 'striped magenta bags contain 1 light orange bag, 4 muted beige bags.',\n",
       " 'light red bags contain 3 shiny yellow bags, 3 faded tan bags, 3 vibrant lime bags, 3 muted coral bags.',\n",
       " 'muted olive bags contain 4 drab coral bags, 5 light salmon bags, 1 vibrant violet bag.',\n",
       " 'clear silver bags contain 1 posh aqua bag, 1 drab teal bag, 4 dark orange bags.',\n",
       " 'faded orange bags contain 4 vibrant purple bags, 4 wavy cyan bags, 1 drab brown bag.',\n",
       " 'mirrored crimson bags contain 5 light aqua bags, 1 wavy olive bag, 2 vibrant lime bags.',\n",
       " 'shiny plum bags contain 2 shiny maroon bags, 3 dark red bags.',\n",
       " 'faded green bags contain 3 striped turquoise bags.',\n",
       " 'bright orange bags contain 1 dull crimson bag, 1 pale lavender bag, 5 shiny aqua bags.',\n",
       " 'dim gray bags contain 2 drab indigo bags, 5 dim turquoise bags.',\n",
       " 'mirrored plum bags contain 1 vibrant red bag, 4 dotted purple bags.',\n",
       " 'posh gold bags contain 4 bright red bags.',\n",
       " 'posh silver bags contain 3 drab coral bags, 1 faded tan bag, 1 bright silver bag, 1 shiny blue bag.',\n",
       " 'dull lime bags contain 5 muted tan bags, 4 mirrored cyan bags.',\n",
       " 'faded turquoise bags contain 2 pale teal bags, 2 bright green bags.',\n",
       " 'bright salmon bags contain 1 dim white bag, 2 clear tomato bags, 1 bright aqua bag.',\n",
       " 'dim gold bags contain 3 mirrored turquoise bags, 5 wavy tomato bags.',\n",
       " 'dull fuchsia bags contain 2 pale beige bags, 1 dotted yellow bag.',\n",
       " 'dark beige bags contain 2 pale magenta bags.',\n",
       " 'dotted maroon bags contain 2 dark tomato bags, 2 light gray bags, 3 faded teal bags, 1 clear gray bag.',\n",
       " 'muted white bags contain 3 dull turquoise bags, 5 dark bronze bags, 1 light olive bag, 3 clear bronze bags.',\n",
       " 'faded blue bags contain 1 dark chartreuse bag, 3 pale aqua bags, 5 faded crimson bags.',\n",
       " 'clear aqua bags contain 3 vibrant olive bags, 5 clear crimson bags.',\n",
       " 'faded cyan bags contain 1 vibrant blue bag, 1 light magenta bag.',\n",
       " 'shiny aqua bags contain 1 clear green bag.',\n",
       " 'bright gray bags contain 2 dim fuchsia bags, 1 striped chartreuse bag, 2 clear aqua bags, 2 dull olive bags.',\n",
       " 'bright white bags contain 2 light purple bags, 5 bright aqua bags.',\n",
       " 'bright lime bags contain 1 pale orange bag, 5 plaid magenta bags, 4 mirrored maroon bags.',\n",
       " 'dark lavender bags contain 5 mirrored bronze bags, 4 dotted aqua bags.',\n",
       " 'striped chartreuse bags contain 3 striped indigo bags, 2 faded plum bags, 4 clear gray bags.',\n",
       " 'muted magenta bags contain 3 clear red bags, 3 dull crimson bags, 1 clear aqua bag, 4 faded tomato bags.',\n",
       " 'clear magenta bags contain 2 striped cyan bags, 5 vibrant lime bags, 4 striped salmon bags.',\n",
       " 'pale yellow bags contain 3 faded fuchsia bags, 2 dotted lime bags, 5 pale gold bags, 1 plaid tomato bag.',\n",
       " 'dull teal bags contain 4 dim green bags, 1 drab maroon bag, 2 dim crimson bags.',\n",
       " 'pale brown bags contain 5 drab orange bags, 2 dotted purple bags, 3 plaid olive bags, 3 pale black bags.',\n",
       " 'posh blue bags contain 4 faded purple bags, 4 drab turquoise bags.',\n",
       " 'pale olive bags contain 5 muted silver bags, 3 mirrored plum bags, 4 vibrant lime bags, 5 striped olive bags.',\n",
       " 'plaid black bags contain 3 posh yellow bags.',\n",
       " 'striped tomato bags contain 4 faded blue bags, 2 shiny magenta bags.',\n",
       " 'wavy tomato bags contain 1 pale gold bag, 2 dim magenta bags.',\n",
       " 'faded plum bags contain 3 light violet bags, 3 posh beige bags, 3 striped aqua bags, 4 dim magenta bags.',\n",
       " 'vibrant turquoise bags contain 3 muted silver bags, 5 dotted black bags.',\n",
       " 'dull white bags contain 5 dim gray bags, 1 faded crimson bag.',\n",
       " 'faded purple bags contain 1 vibrant orange bag, 4 pale crimson bags, 5 shiny blue bags, 1 light gold bag.',\n",
       " 'clear white bags contain 1 striped orange bag, 3 pale coral bags, 5 plaid chartreuse bags.',\n",
       " 'striped maroon bags contain 2 wavy olive bags.',\n",
       " 'light tomato bags contain 2 pale crimson bags, 3 bright fuchsia bags, 2 pale salmon bags, 3 pale olive bags.',\n",
       " 'drab tomato bags contain 1 pale olive bag.',\n",
       " 'dark aqua bags contain 1 shiny magenta bag, 4 faded lime bags, 4 faded gold bags.',\n",
       " 'plaid bronze bags contain 2 pale purple bags.',\n",
       " 'dark plum bags contain 3 wavy brown bags, 1 bright salmon bag.',\n",
       " 'dark purple bags contain 4 dotted red bags.',\n",
       " 'light teal bags contain 1 vibrant indigo bag, 5 wavy olive bags, 4 clear maroon bags, 1 light silver bag.',\n",
       " 'drab fuchsia bags contain 3 faded turquoise bags, 5 dim yellow bags.',\n",
       " 'light turquoise bags contain 1 dotted blue bag, 4 mirrored tomato bags.',\n",
       " 'clear maroon bags contain 4 mirrored green bags.',\n",
       " 'posh maroon bags contain 3 dim black bags, 3 bright gold bags, 3 mirrored white bags, 1 clear lavender bag.',\n",
       " 'dotted blue bags contain 2 wavy maroon bags.',\n",
       " 'bright tan bags contain 4 faded turquoise bags, 5 drab coral bags, 5 dull red bags, 2 dim gray bags.',\n",
       " 'dark salmon bags contain 4 clear fuchsia bags, 5 mirrored red bags.',\n",
       " 'mirrored fuchsia bags contain 4 bright tomato bags, 3 vibrant orange bags.',\n",
       " 'vibrant green bags contain 1 clear lavender bag.',\n",
       " 'dim white bags contain 5 dull red bags.',\n",
       " 'light white bags contain 3 dark purple bags, 1 mirrored fuchsia bag, 1 plaid gold bag, 1 posh lime bag.',\n",
       " 'dark turquoise bags contain 3 striped green bags, 1 dull gold bag, 2 pale gray bags.',\n",
       " 'light purple bags contain 5 muted brown bags, 5 muted purple bags, 4 dull yellow bags, 5 vibrant gold bags.',\n",
       " 'posh lavender bags contain 5 posh yellow bags, 4 plaid plum bags, 1 dark fuchsia bag, 1 bright maroon bag.',\n",
       " 'posh crimson bags contain 1 vibrant gold bag, 5 clear green bags, 2 posh chartreuse bags.',\n",
       " 'wavy lime bags contain 5 mirrored beige bags.',\n",
       " 'wavy black bags contain 1 plaid orange bag, 4 shiny green bags, 3 shiny blue bags, 4 muted red bags.',\n",
       " 'muted red bags contain 4 vibrant lime bags, 2 drab black bags, 4 vibrant red bags, 5 faded beige bags.',\n",
       " 'vibrant gold bags contain 2 bright silver bags, 4 faded teal bags, 2 vibrant orange bags, 3 striped salmon bags.',\n",
       " 'shiny crimson bags contain 2 bright yellow bags.',\n",
       " 'muted turquoise bags contain 5 bright plum bags.',\n",
       " 'posh orange bags contain 4 vibrant yellow bags, 5 clear crimson bags.',\n",
       " 'wavy aqua bags contain 5 shiny green bags, 5 bright fuchsia bags, 4 muted fuchsia bags.',\n",
       " 'clear green bags contain 4 dotted plum bags, 2 vibrant olive bags, 5 pale beige bags.',\n",
       " 'pale aqua bags contain 3 dark tomato bags, 5 posh lime bags.',\n",
       " 'drab maroon bags contain 5 bright magenta bags, 2 bright plum bags, 5 clear green bags, 3 faded tomato bags.',\n",
       " 'vibrant plum bags contain 3 light crimson bags, 5 dotted silver bags, 5 mirrored red bags, 1 dotted turquoise bag.',\n",
       " 'posh yellow bags contain 5 plaid lavender bags, 5 dim tomato bags.',\n",
       " 'faded brown bags contain 1 striped orange bag, 5 wavy green bags.',\n",
       " 'drab cyan bags contain 4 faded teal bags, 3 vibrant aqua bags, 2 light chartreuse bags, 3 dark orange bags.',\n",
       " 'dark lime bags contain 4 vibrant blue bags.',\n",
       " 'faded coral bags contain 4 wavy green bags, 4 mirrored gold bags, 3 striped fuchsia bags, 1 pale fuchsia bag.',\n",
       " 'dark orange bags contain 1 dotted red bag, 2 vibrant red bags.',\n",
       " 'wavy magenta bags contain 3 dull chartreuse bags, 2 dim maroon bags, 2 clear maroon bags.',\n",
       " 'plaid coral bags contain 4 drab tan bags, 1 pale tan bag.',\n",
       " 'mirrored salmon bags contain 1 muted bronze bag, 5 muted purple bags.',\n",
       " 'dim tomato bags contain 2 drab silver bags, 4 mirrored purple bags, 1 dull olive bag, 5 dotted purple bags.',\n",
       " 'wavy gold bags contain 3 dark crimson bags, 1 dim white bag.',\n",
       " 'light fuchsia bags contain 3 mirrored green bags, 2 wavy fuchsia bags.',\n",
       " 'pale tomato bags contain 4 clear purple bags, 5 faded brown bags, 4 light coral bags.',\n",
       " 'faded yellow bags contain 5 wavy olive bags, 2 pale lavender bags, 4 bright plum bags.',\n",
       " 'light violet bags contain 1 dotted red bag, 4 dim aqua bags.',\n",
       " 'posh lime bags contain 2 pale crimson bags, 1 pale gold bag, 1 shiny blue bag, 4 muted gray bags.',\n",
       " 'mirrored silver bags contain 4 striped bronze bags, 3 faded salmon bags, 3 drab green bags, 4 striped green bags.',\n",
       " 'dark green bags contain 5 striped maroon bags, 3 dim olive bags, 4 vibrant chartreuse bags, 5 dim white bags.',\n",
       " 'mirrored olive bags contain 2 dotted red bags, 5 dim white bags.',\n",
       " 'dark teal bags contain 3 wavy olive bags, 3 pale crimson bags.',\n",
       " 'pale tan bags contain 2 dark orange bags, 5 bright plum bags, 4 pale crimson bags.',\n",
       " 'wavy plum bags contain 3 dull lime bags.',\n",
       " 'light indigo bags contain 5 dark magenta bags.',\n",
       " 'drab lime bags contain 1 bright fuchsia bag, 4 wavy brown bags.',\n",
       " 'drab tan bags contain 3 bright tomato bags, 1 muted green bag.',\n",
       " 'vibrant indigo bags contain 5 dull chartreuse bags, 5 clear aqua bags.',\n",
       " 'dark bronze bags contain 3 dull red bags, 3 mirrored maroon bags, 1 muted green bag.',\n",
       " 'shiny red bags contain 2 dark bronze bags, 4 faded magenta bags, 5 dull teal bags.',\n",
       " 'shiny black bags contain 3 vibrant olive bags, 2 plaid lime bags, 5 shiny gold bags, 2 dotted plum bags.',\n",
       " 'light gold bags contain 5 vibrant olive bags.',\n",
       " 'light plum bags contain 5 clear gray bags, 5 dotted chartreuse bags, 4 plaid red bags, 1 plaid lime bag.',\n",
       " 'bright violet bags contain 4 bright maroon bags, 5 posh red bags, 2 faded olive bags, 4 dim gray bags.',\n",
       " 'faded red bags contain 4 drab maroon bags, 4 vibrant violet bags, 1 faded purple bag, 2 dotted black bags.',\n",
       " 'muted orange bags contain 4 plaid chartreuse bags, 5 muted lavender bags, 2 faded purple bags.',\n",
       " 'clear coral bags contain 2 drab teal bags, 5 bright turquoise bags.',\n",
       " 'wavy orange bags contain 4 muted cyan bags, 3 light indigo bags, 5 bright black bags, 5 light salmon bags.',\n",
       " 'faded fuchsia bags contain 3 pale gold bags, 3 faded salmon bags, 4 pale red bags.',\n",
       " 'light brown bags contain 4 pale silver bags, 4 clear tan bags.',\n",
       " 'shiny gray bags contain 3 muted teal bags, 1 bright purple bag, 2 bright olive bags, 4 mirrored green bags.',\n",
       " 'bright brown bags contain 2 dark teal bags, 5 light plum bags, 2 plaid olive bags, 5 dark chartreuse bags.',\n",
       " 'mirrored white bags contain 1 wavy gray bag, 3 bright tomato bags, 1 muted silver bag, 4 striped olive bags.',\n",
       " 'pale magenta bags contain 1 clear gray bag, 1 muted gray bag, 1 wavy cyan bag, 4 dull brown bags.',\n",
       " 'bright magenta bags contain 2 muted tan bags, 1 pale gold bag, 2 wavy cyan bags, 4 vibrant orange bags.',\n",
       " 'clear teal bags contain 1 dark teal bag, 2 vibrant lime bags.',\n",
       " 'light orange bags contain 3 light gold bags, 4 clear plum bags, 4 dotted indigo bags.',\n",
       " 'plaid cyan bags contain 1 pale magenta bag.',\n",
       " 'wavy chartreuse bags contain 2 posh green bags, 5 dotted purple bags, 2 dark tomato bags, 3 muted gray bags.',\n",
       " 'light coral bags contain 5 clear gray bags, 2 posh purple bags, 2 mirrored violet bags.',\n",
       " 'dull violet bags contain 3 dotted blue bags, 5 mirrored tomato bags, 1 dull chartreuse bag, 2 posh beige bags.',\n",
       " 'bright tomato bags contain 3 vibrant red bags, 3 muted gray bags.',\n",
       " 'mirrored magenta bags contain 4 wavy brown bags.',\n",
       " 'muted indigo bags contain 4 wavy chartreuse bags, 3 vibrant indigo bags, 2 posh magenta bags, 1 plaid crimson bag.',\n",
       " 'bright maroon bags contain 2 dull violet bags, 2 faded tan bags, 3 striped gray bags, 5 pale magenta bags.',\n",
       " 'dark tomato bags contain no other bags.',\n",
       " 'pale fuchsia bags contain 3 drab silver bags, 4 faded purple bags, 2 mirrored cyan bags, 5 dark bronze bags.',\n",
       " 'dull black bags contain 1 dull indigo bag, 1 wavy brown bag, 5 striped gray bags.',\n",
       " 'pale white bags contain 3 light gray bags, 2 plaid lavender bags, 1 wavy maroon bag.',\n",
       " 'shiny turquoise bags contain 4 pale red bags.',\n",
       " 'drab brown bags contain 5 mirrored plum bags, 4 dotted red bags.',\n",
       " 'bright green bags contain 1 dull lime bag, 2 clear lavender bags.',\n",
       " 'wavy blue bags contain 4 dotted purple bags.',\n",
       " 'muted aqua bags contain 5 faded plum bags, 3 plaid plum bags, 4 dotted tan bags, 1 clear gray bag.',\n",
       " 'clear yellow bags contain 4 dotted indigo bags, 3 vibrant aqua bags, 4 vibrant orange bags.',\n",
       " 'mirrored gray bags contain 4 shiny crimson bags, 2 mirrored coral bags, 1 dotted tan bag, 4 posh cyan bags.',\n",
       " 'dark maroon bags contain 1 dark salmon bag, 3 muted coral bags.',\n",
       " 'posh plum bags contain 1 mirrored bronze bag, 4 plaid purple bags, 3 vibrant white bags.',\n",
       " 'bright teal bags contain 2 pale aqua bags, 1 mirrored black bag.',\n",
       " 'wavy teal bags contain 5 plaid tan bags, 3 dull black bags, 1 bright teal bag, 3 clear teal bags.',\n",
       " 'dotted magenta bags contain 1 plaid plum bag, 5 plaid salmon bags, 3 light gold bags.',\n",
       " 'faded tomato bags contain 1 dark bronze bag, 2 faded purple bags, 4 vibrant red bags, 4 pale lavender bags.',\n",
       " 'dull blue bags contain 3 dotted bronze bags, 2 shiny olive bags, 3 muted gold bags.',\n",
       " 'posh aqua bags contain 5 vibrant orange bags, 1 vibrant olive bag.',\n",
       " 'mirrored black bags contain 3 dark teal bags, 4 plaid chartreuse bags, 2 light salmon bags, 2 vibrant white bags.',\n",
       " 'wavy violet bags contain 5 vibrant indigo bags.',\n",
       " 'vibrant blue bags contain 4 shiny olive bags, 4 light olive bags, 2 muted green bags.',\n",
       " 'dotted green bags contain 3 shiny violet bags, 3 posh black bags, 3 dark lime bags.',\n",
       " 'wavy cyan bags contain 2 muted gray bags, 3 vibrant olive bags, 4 striped olive bags, 4 drab silver bags.',\n",
       " 'faded maroon bags contain 5 bright yellow bags, 2 bright tomato bags, 5 mirrored magenta bags.',\n",
       " 'dull olive bags contain 1 bright plum bag, 2 pale crimson bags.',\n",
       " 'clear lime bags contain 5 striped blue bags, 5 wavy blue bags, 3 drab tan bags, 1 shiny olive bag.',\n",
       " 'striped yellow bags contain 1 mirrored red bag.',\n",
       " 'plaid magenta bags contain 2 clear yellow bags, 1 pale coral bag, 3 muted bronze bags.',\n",
       " 'light lime bags contain 1 dim turquoise bag.',\n",
       " 'striped brown bags contain 3 mirrored brown bags, 4 clear cyan bags, 5 bright white bags, 1 muted maroon bag.',\n",
       " 'dotted indigo bags contain 3 light olive bags, 1 dull chartreuse bag.',\n",
       " 'shiny tan bags contain 2 dull lime bags, 5 shiny black bags, 5 dull teal bags.',\n",
       " 'clear olive bags contain 5 drab coral bags, 4 striped aqua bags, 4 dotted lavender bags.',\n",
       " 'plaid chartreuse bags contain 1 plaid red bag, 4 faded tomato bags.',\n",
       " 'dotted olive bags contain 2 dull yellow bags.',\n",
       " 'faded lime bags contain 5 dotted aqua bags, 4 shiny silver bags, 4 muted white bags.',\n",
       " 'vibrant silver bags contain 4 dotted teal bags, 3 posh olive bags.',\n",
       " 'striped beige bags contain 2 vibrant white bags, 3 dark gold bags, 4 posh violet bags, 4 bright chartreuse bags.',\n",
       " 'dim plum bags contain 2 striped indigo bags, 2 vibrant gold bags.',\n",
       " 'clear crimson bags contain 5 vibrant red bags.',\n",
       " 'plaid maroon bags contain 4 clear crimson bags.',\n",
       " 'drab coral bags contain 2 plaid plum bags.',\n",
       " 'dull bronze bags contain 4 pale black bags, 1 dull tan bag, 5 dull cyan bags, 4 pale lavender bags.',\n",
       " 'wavy bronze bags contain 4 posh coral bags, 2 bright silver bags.',\n",
       " 'dull aqua bags contain 3 dotted orange bags, 3 pale teal bags.',\n",
       " 'muted plum bags contain 1 light blue bag, 2 muted maroon bags, 4 dull olive bags.',\n",
       " 'vibrant tan bags contain 4 drab teal bags.',\n",
       " 'dull tomato bags contain 5 dull white bags.',\n",
       " 'muted yellow bags contain 3 dark yellow bags, 5 faded beige bags.',\n",
       " 'shiny white bags contain 4 bright silver bags.',\n",
       " 'muted crimson bags contain 1 clear maroon bag.',\n",
       " 'muted violet bags contain 3 dotted yellow bags, 1 light indigo bag, 4 mirrored black bags, 5 drab lime bags.',\n",
       " 'posh white bags contain 3 faded brown bags, 2 dull yellow bags.',\n",
       " 'wavy crimson bags contain 3 shiny black bags, 2 dotted blue bags, 4 dark maroon bags.',\n",
       " 'clear salmon bags contain 1 mirrored magenta bag, 4 bright chartreuse bags, 5 vibrant black bags, 2 vibrant chartreuse bags.',\n",
       " 'pale teal bags contain 5 mirrored white bags, 2 plaid orange bags, 4 muted lime bags.',\n",
       " 'light aqua bags contain 2 shiny salmon bags, 3 dark tomato bags, 1 mirrored purple bag.',\n",
       " 'clear beige bags contain 1 muted crimson bag.',\n",
       " 'vibrant olive bags contain 5 dark tomato bags, 1 pale gold bag, 4 muted tan bags.',\n",
       " 'plaid brown bags contain 3 mirrored lavender bags, 1 muted crimson bag, 3 muted green bags, 1 bright lavender bag.',\n",
       " 'dim magenta bags contain 4 pale fuchsia bags, 3 drab black bags, 4 plaid orange bags.',\n",
       " 'bright purple bags contain 3 muted gray bags, 3 pale coral bags.',\n",
       " 'posh indigo bags contain 2 bright beige bags, 2 dim tomato bags.',\n",
       " 'drab lavender bags contain 2 dotted chartreuse bags, 1 posh green bag, 3 light silver bags, 1 dotted black bag.',\n",
       " 'pale crimson bags contain no other bags.',\n",
       " 'posh gray bags contain 1 muted green bag.',\n",
       " 'shiny lime bags contain 3 mirrored maroon bags, 1 posh crimson bag, 4 mirrored orange bags, 2 posh olive bags.',\n",
       " 'muted beige bags contain 1 posh tan bag, 3 posh olive bags, 1 faded white bag, 2 posh green bags.',\n",
       " 'light black bags contain 3 striped green bags, 2 pale salmon bags, 3 muted crimson bags.',\n",
       " 'dark gold bags contain 5 striped maroon bags, 2 pale fuchsia bags, 3 light gold bags.',\n",
       " 'light bronze bags contain 2 clear purple bags, 4 dim crimson bags.',\n",
       " 'muted blue bags contain 1 faded gray bag, 4 muted salmon bags, 5 dull bronze bags.',\n",
       " 'vibrant orange bags contain no other bags.',\n",
       " 'dim lavender bags contain 1 vibrant indigo bag.',\n",
       " 'posh fuchsia bags contain 3 clear fuchsia bags, 2 shiny green bags, 3 plaid plum bags.',\n",
       " 'dim tan bags contain 5 pale plum bags, 3 posh gray bags, 1 clear yellow bag.',\n",
       " 'pale lime bags contain no other bags.',\n",
       " 'striped blue bags contain 5 pale black bags.',\n",
       " 'shiny tomato bags contain 1 dim fuchsia bag, 5 faded blue bags, 3 muted brown bags, 3 mirrored salmon bags.',\n",
       " 'dotted orange bags contain 4 bright tomato bags, 1 light silver bag.',\n",
       " 'muted tan bags contain no other bags.',\n",
       " 'pale black bags contain 2 dull brown bags, 4 mirrored chartreuse bags, 2 dim aqua bags.',\n",
       " 'shiny purple bags contain 3 dotted indigo bags, 5 vibrant gold bags, 2 light chartreuse bags, 4 clear magenta bags.',\n",
       " 'dull brown bags contain 2 bright beige bags, 4 vibrant orange bags, 2 bright tomato bags, 4 clear lavender bags.',\n",
       " 'plaid aqua bags contain 3 plaid indigo bags.',\n",
       " 'dark olive bags contain 1 pale plum bag, 4 dim maroon bags.',\n",
       " 'dark silver bags contain 3 shiny blue bags, 2 muted gray bags, 4 drab coral bags.',\n",
       " 'clear turquoise bags contain 5 light violet bags, 3 drab yellow bags.',\n",
       " 'wavy brown bags contain 3 shiny coral bags, 3 shiny salmon bags, 1 drab magenta bag.',\n",
       " 'dim indigo bags contain 5 bright green bags.',\n",
       " 'mirrored gold bags contain 1 plaid magenta bag, 2 plaid gold bags, 4 light turquoise bags.',\n",
       " 'drab red bags contain 3 mirrored bronze bags.',\n",
       " 'faded bronze bags contain 1 vibrant aqua bag, 2 clear tomato bags, 2 dull tan bags.',\n",
       " 'bright lavender bags contain 4 drab coral bags, 1 bright green bag.',\n",
       " 'wavy lavender bags contain 2 wavy green bags, 4 drab silver bags, 5 light turquoise bags.',\n",
       " 'wavy salmon bags contain 2 dotted gray bags, 4 bright chartreuse bags, 4 striped gray bags.',\n",
       " 'dotted yellow bags contain 4 dark salmon bags, 1 posh tan bag, 4 drab tomato bags, 4 vibrant chartreuse bags.',\n",
       " 'dull turquoise bags contain 5 drab silver bags, 1 dark orange bag.',\n",
       " 'pale gray bags contain 4 dull aqua bags, 4 faded gold bags, 2 mirrored orange bags, 2 dim magenta bags.',\n",
       " 'dark red bags contain 2 bright gray bags, 4 bright black bags.',\n",
       " 'dim fuchsia bags contain 3 bright magenta bags, 5 pale crimson bags.',\n",
       " 'vibrant lime bags contain 2 wavy maroon bags, 2 pale magenta bags, 4 pale crimson bags, 3 drab orange bags.',\n",
       " 'bright bronze bags contain 4 vibrant black bags, 3 drab fuchsia bags, 3 striped cyan bags, 3 dotted blue bags.',\n",
       " 'muted coral bags contain 3 wavy white bags, 1 plaid tan bag.',\n",
       " 'wavy white bags contain 2 drab maroon bags.',\n",
       " 'pale coral bags contain 3 dotted bronze bags, 1 dull gold bag.',\n",
       " 'drab white bags contain 3 drab silver bags, 3 bright tomato bags, 1 bright silver bag.',\n",
       " 'light olive bags contain 3 muted tan bags, 2 mirrored tomato bags.',\n",
       " 'mirrored tomato bags contain 2 dark tomato bags, 3 shiny gold bags.',\n",
       " 'light crimson bags contain 4 clear magenta bags, 2 plaid coral bags, 5 dull chartreuse bags, 5 dark teal bags.',\n",
       " 'bright cyan bags contain 1 clear chartreuse bag, 1 striped brown bag, 5 light tomato bags, 4 dark coral bags.',\n",
       " 'vibrant fuchsia bags contain 3 dull white bags, 1 dim purple bag, 5 shiny yellow bags.',\n",
       " 'drab gold bags contain 5 wavy chartreuse bags.',\n",
       " 'plaid yellow bags contain 4 faded plum bags, 1 faded indigo bag, 2 drab purple bags, 1 light purple bag.',\n",
       " 'bright black bags contain 2 clear yellow bags, 1 dotted red bag, 4 dim white bags.',\n",
       " 'pale maroon bags contain 2 vibrant tomato bags, 3 mirrored tomato bags.',\n",
       " 'wavy gray bags contain 2 wavy cyan bags, 2 dark tomato bags, 4 vibrant orange bags, 5 pale silver bags.',\n",
       " 'faded salmon bags contain 4 bright plum bags.',\n",
       " 'shiny teal bags contain 4 dark magenta bags.',\n",
       " 'dim bronze bags contain 5 striped olive bags, 5 dotted plum bags, 4 dark purple bags.',\n",
       " 'dotted lavender bags contain 4 striped indigo bags, 2 mirrored red bags, 2 bright chartreuse bags, 4 bright teal bags.',\n",
       " 'plaid beige bags contain 4 vibrant green bags, 3 striped violet bags, 5 vibrant blue bags.',\n",
       " 'dull purple bags contain 1 dark beige bag, 1 drab silver bag, 4 faded fuchsia bags, 2 vibrant olive bags.',\n",
       " 'bright olive bags contain 3 faded salmon bags, 1 wavy magenta bag, 5 dim yellow bags.',\n",
       " 'mirrored maroon bags contain 3 bright magenta bags, 5 pale lime bags, 3 striped olive bags.',\n",
       " 'clear brown bags contain 2 mirrored orange bags, 5 bright cyan bags.',\n",
       " 'drab teal bags contain 3 dull olive bags.',\n",
       " 'clear red bags contain 1 bright maroon bag.',\n",
       " 'vibrant black bags contain 4 pale fuchsia bags, 3 clear lavender bags, 2 shiny blue bags, 3 dotted blue bags.',\n",
       " 'faded white bags contain 3 wavy coral bags, 4 faded yellow bags, 5 shiny olive bags, 1 plaid orange bag.',\n",
       " 'dotted aqua bags contain 1 wavy white bag, 3 dotted blue bags, 5 pale lavender bags, 4 clear aqua bags.',\n",
       " 'pale blue bags contain 3 dim salmon bags, 3 muted cyan bags, 5 pale fuchsia bags.',\n",
       " 'dim turquoise bags contain 4 vibrant chartreuse bags, 2 dark silver bags, 3 pale gold bags.',\n",
       " 'dull magenta bags contain 3 muted salmon bags, 4 dotted gray bags, 3 light salmon bags.',\n",
       " 'dotted coral bags contain 2 mirrored tomato bags, 1 vibrant teal bag, 3 dull crimson bags.',\n",
       " 'dull beige bags contain 2 faded fuchsia bags.',\n",
       " 'shiny gold bags contain 4 bright beige bags, 3 dull crimson bags, 4 mirrored maroon bags, 3 bright tomato bags.',\n",
       " 'pale indigo bags contain 2 dotted teal bags, 3 faded teal bags, 4 wavy indigo bags.',\n",
       " 'shiny magenta bags contain 5 bright tomato bags, 5 dull lime bags, 5 mirrored bronze bags, 2 dim black bags.',\n",
       " 'muted cyan bags contain 2 dark bronze bags, 5 drab silver bags, 4 dotted chartreuse bags.',\n",
       " 'plaid orange bags contain 4 light plum bags, 5 shiny salmon bags, 5 posh beige bags.',\n",
       " 'shiny green bags contain 5 dotted tan bags, 5 mirrored olive bags, 1 dark teal bag.',\n",
       " 'dull maroon bags contain 1 striped black bag, 4 clear green bags.',\n",
       " 'drab aqua bags contain 1 striped indigo bag, 3 vibrant white bags.',\n",
       " 'bright gold bags contain 4 mirrored beige bags, 4 mirrored yellow bags.',\n",
       " 'plaid tan bags contain 5 shiny aqua bags.',\n",
       " 'striped plum bags contain 4 clear magenta bags, 2 dark gold bags.',\n",
       " 'vibrant teal bags contain 1 dim aqua bag, 4 vibrant violet bags, 3 plaid olive bags, 1 mirrored olive bag.',\n",
       " 'posh bronze bags contain 5 dark tomato bags, 5 shiny silver bags.',\n",
       " 'dim orange bags contain 4 dull salmon bags.',\n",
       " 'striped indigo bags contain 4 drab magenta bags.',\n",
       " 'vibrant yellow bags contain 4 drab olive bags, 4 wavy olive bags, 2 dark teal bags, 2 faded purple bags.',\n",
       " 'striped purple bags contain 5 pale red bags.',\n",
       " 'dim coral bags contain 1 plaid maroon bag, 2 pale magenta bags, 1 pale indigo bag, 2 dotted turquoise bags.',\n",
       " 'muted silver bags contain 4 mirrored turquoise bags.',\n",
       " 'posh cyan bags contain 3 dotted purple bags.',\n",
       " 'plaid lavender bags contain 3 muted gray bags, 1 light plum bag.',\n",
       " 'faded tan bags contain 1 mirrored cyan bag, 2 plaid crimson bags, 5 mirrored maroon bags.',\n",
       " 'clear lavender bags contain 4 pale gold bags, 1 posh lime bag, 4 pale crimson bags.',\n",
       " 'dull gray bags contain 5 shiny crimson bags, 5 wavy cyan bags, 3 posh lavender bags.',\n",
       " 'dull green bags contain 1 faded bronze bag, 3 vibrant indigo bags, 2 muted fuchsia bags, 4 dotted silver bags.',\n",
       " 'dark magenta bags contain 3 wavy white bags, 3 plaid plum bags, 4 wavy lavender bags, 3 drab magenta bags.',\n",
       " 'plaid red bags contain 1 bright turquoise bag.',\n",
       " 'dull coral bags contain 4 clear tomato bags.',\n",
       " 'posh turquoise bags contain 5 dull gold bags, 4 mirrored chartreuse bags.',\n",
       " 'drab crimson bags contain 2 dull tomato bags, 5 posh orange bags, 5 shiny violet bags.',\n",
       " 'clear tan bags contain 1 pale fuchsia bag, 4 light aqua bags, 3 shiny blue bags, 3 bright turquoise bags.',\n",
       " 'dotted brown bags contain 4 drab magenta bags, 5 plaid crimson bags, 2 posh beige bags.',\n",
       " 'light silver bags contain 3 mirrored green bags, 5 mirrored maroon bags, 5 shiny blue bags.',\n",
       " 'dotted gold bags contain 2 dim magenta bags.',\n",
       " 'drab yellow bags contain 5 pale purple bags.',\n",
       " 'faded lavender bags contain 5 muted cyan bags.',\n",
       " 'vibrant beige bags contain 4 clear turquoise bags, 2 dark fuchsia bags, 1 pale gray bag, 5 dim beige bags.',\n",
       " 'clear fuchsia bags contain 1 pale fuchsia bag, 1 wavy turquoise bag, 5 faded gray bags.',\n",
       " 'shiny chartreuse bags contain 4 vibrant green bags, 1 dotted teal bag.',\n",
       " 'dim purple bags contain 1 bright turquoise bag.',\n",
       " 'clear indigo bags contain 4 light white bags, 3 vibrant orange bags.',\n",
       " 'wavy turquoise bags contain 5 bright magenta bags.',\n",
       " 'vibrant chartreuse bags contain 4 mirrored chartreuse bags, 2 muted tan bags, 2 plaid lime bags, 3 striped olive bags.',\n",
       " 'dark chartreuse bags contain 5 shiny blue bags.',\n",
       " 'clear plum bags contain 3 pale lime bags.',\n",
       " 'dotted tomato bags contain 5 bright red bags, 2 bright olive bags, 5 drab silver bags, 4 clear magenta bags.',\n",
       " 'mirrored beige bags contain 4 light violet bags, 5 mirrored salmon bags, 4 dim yellow bags, 5 bright yellow bags.',\n",
       " 'posh teal bags contain 2 plaid turquoise bags, 3 pale salmon bags, 1 striped plum bag.',\n",
       " 'dull chartreuse bags contain 5 pale lavender bags, 1 bright turquoise bag, 3 pale beige bags.',\n",
       " 'mirrored lavender bags contain 4 vibrant tomato bags, 2 plaid tan bags, 5 bright magenta bags.',\n",
       " 'dark gray bags contain 5 wavy turquoise bags, 4 wavy gray bags, 4 dark bronze bags, 4 pale aqua bags.',\n",
       " 'dark white bags contain 4 clear maroon bags, 2 vibrant olive bags, 1 dull lime bag, 1 faded lime bag.',\n",
       " 'dull indigo bags contain 4 clear fuchsia bags, 3 dotted tan bags, 1 plaid cyan bag.',\n",
       " 'striped tan bags contain 3 pale brown bags.',\n",
       " 'dull gold bags contain 2 dark yellow bags, 3 dull olive bags.',\n",
       " 'light lavender bags contain 2 plaid red bags, 5 dotted purple bags, 1 bright beige bag, 3 pale beige bags.',\n",
       " 'faded teal bags contain 4 mirrored olive bags.',\n",
       " 'plaid salmon bags contain 1 dark bronze bag, 5 pale yellow bags, 1 striped cyan bag, 2 muted cyan bags.',\n",
       " 'dotted purple bags contain 1 bright turquoise bag, 1 posh green bag.',\n",
       " 'dull silver bags contain 3 striped salmon bags, 4 posh violet bags, 4 striped orange bags.',\n",
       " 'drab chartreuse bags contain 4 pale lavender bags.',\n",
       " 'striped coral bags contain 5 bright gray bags, 4 dark teal bags, 5 dotted purple bags.',\n",
       " 'wavy olive bags contain no other bags.',\n",
       " 'plaid olive bags contain 1 pale black bag, 3 clear plum bags.',\n",
       " 'drab black bags contain 3 striped olive bags, 2 mirrored chartreuse bags, 5 pale silver bags.',\n",
       " 'striped lime bags contain 3 dark chartreuse bags, 5 pale silver bags, 2 plaid crimson bags, 4 clear fuchsia bags.',\n",
       " 'drab beige bags contain 4 dim black bags, 4 striped black bags, 4 dull crimson bags, 5 dark gray bags.',\n",
       " 'muted tomato bags contain 3 light bronze bags, 3 pale salmon bags, 2 vibrant chartreuse bags.',\n",
       " 'bright fuchsia bags contain 5 drab orange bags, 3 pale black bags, 3 mirrored white bags, 5 faded tomato bags.',\n",
       " 'vibrant gray bags contain 4 posh lime bags, 2 dark purple bags, 4 clear aqua bags.',\n",
       " 'shiny yellow bags contain 5 bright beige bags, 2 vibrant red bags, 5 dim yellow bags, 2 vibrant yellow bags.',\n",
       " 'posh coral bags contain 5 drab indigo bags.',\n",
       " 'muted fuchsia bags contain 5 shiny silver bags, 2 dotted salmon bags, 1 muted tan bag.',\n",
       " 'muted brown bags contain 4 clear maroon bags, 5 dim purple bags, 4 wavy maroon bags, 2 muted red bags.',\n",
       " 'posh chartreuse bags contain 5 muted tan bags, 3 drab teal bags.',\n",
       " 'vibrant brown bags contain 1 wavy bronze bag, 5 bright red bags, 4 muted fuchsia bags, 4 clear fuchsia bags.',\n",
       " 'posh purple bags contain 2 drab turquoise bags, 5 striped blue bags, 1 muted cyan bag.',\n",
       " 'plaid lime bags contain 3 muted gray bags, 5 vibrant red bags, 1 wavy gray bag, 1 pale silver bag.',\n",
       " 'posh violet bags contain 2 faded crimson bags, 1 shiny olive bag, 3 bright magenta bags, 1 drab silver bag.',\n",
       " 'striped gold bags contain 5 faded salmon bags, 2 drab bronze bags, 2 dark plum bags.',\n",
       " 'striped gray bags contain 2 mirrored crimson bags, 5 faded beige bags, 1 dull red bag.',\n",
       " 'dim blue bags contain 2 dark coral bags, 3 dim yellow bags, 1 dull salmon bag.',\n",
       " 'bright silver bags contain 2 mirrored tomato bags, 3 bright plum bags, 4 pale lavender bags, 1 clear tomato bag.',\n",
       " 'striped red bags contain 4 light yellow bags, 5 mirrored white bags, 5 plaid gold bags.',\n",
       " 'shiny maroon bags contain 3 wavy cyan bags, 1 mirrored tomato bag, 1 mirrored coral bag.',\n",
       " 'mirrored brown bags contain 2 mirrored olive bags, 3 mirrored green bags, 1 dim tomato bag.',\n",
       " 'striped olive bags contain no other bags.',\n",
       " 'striped violet bags contain 5 bright tomato bags.',\n",
       " 'mirrored aqua bags contain 4 dark gray bags, 5 shiny blue bags, 2 pale silver bags.',\n",
       " 'plaid white bags contain 3 dim maroon bags, 2 dim tan bags.',\n",
       " 'drab orange bags contain 5 striped olive bags.',\n",
       " 'dark brown bags contain 2 mirrored bronze bags, 5 clear maroon bags, 2 dull lime bags.',\n",
       " 'dotted silver bags contain 1 dark gold bag, 1 drab black bag, 3 pale aqua bags.',\n",
       " 'pale plum bags contain 5 striped maroon bags, 5 dotted purple bags, 4 shiny magenta bags.',\n",
       " 'faded indigo bags contain 1 posh cyan bag, 5 bright green bags.',\n",
       " 'mirrored teal bags contain 3 muted indigo bags, 4 clear fuchsia bags, 4 vibrant teal bags, 5 drab violet bags.',\n",
       " 'shiny lavender bags contain 5 striped beige bags, 2 dull magenta bags, 4 clear tan bags.',\n",
       " 'pale beige bags contain 5 mirrored maroon bags.',\n",
       " 'striped bronze bags contain 1 pale orange bag, 5 shiny cyan bags, 5 plaid purple bags, 1 vibrant chartreuse bag.',\n",
       " 'faded gold bags contain 3 pale brown bags, 2 dull violet bags, 2 clear maroon bags, 4 dull lime bags.',\n",
       " 'clear tomato bags contain 4 vibrant orange bags, 3 bright tomato bags, 3 wavy chartreuse bags, 5 wavy olive bags.',\n",
       " 'pale red bags contain 5 wavy blue bags, 5 dark purple bags, 1 bright tomato bag, 4 dark tan bags.',\n",
       " 'vibrant red bags contain 5 wavy gray bags, 5 dark tomato bags.',\n",
       " 'dim salmon bags contain 2 faded crimson bags.',\n",
       " 'shiny blue bags contain 4 muted tan bags, 2 vibrant orange bags.',\n",
       " 'vibrant white bags contain 3 mirrored cyan bags.',\n",
       " 'dark violet bags contain 5 vibrant blue bags, 3 wavy tomato bags.',\n",
       " 'pale gold bags contain no other bags.',\n",
       " 'dim silver bags contain 4 drab tan bags, 4 pale silver bags, 5 clear bronze bags, 4 drab maroon bags.',\n",
       " 'drab blue bags contain 5 vibrant indigo bags, 3 muted turquoise bags.',\n",
       " 'drab plum bags contain 2 dim turquoise bags, 2 drab violet bags, 1 light gray bag, 3 clear tan bags.',\n",
       " 'bright plum bags contain 3 wavy olive bags.',\n",
       " 'dark fuchsia bags contain 4 dotted indigo bags, 3 dark brown bags, 1 clear white bag.',\n",
       " 'bright turquoise bags contain 1 posh lime bag, 2 wavy olive bags, 1 pale crimson bag.',\n",
       " 'dotted turquoise bags contain 3 faded plum bags, 1 bright tomato bag.',\n",
       " 'shiny indigo bags contain 1 wavy chartreuse bag.',\n",
       " 'dark yellow bags contain 2 light gold bags.',\n",
       " 'posh olive bags contain 2 shiny indigo bags.',\n",
       " 'light chartreuse bags contain 5 drab turquoise bags, 2 faded purple bags, 3 faded gray bags.',\n",
       " 'vibrant tomato bags contain 3 light olive bags, 4 shiny purple bags.',\n",
       " 'posh brown bags contain 4 shiny green bags, 1 pale purple bag.',\n",
       " 'bright chartreuse bags contain 3 light gold bags.',\n",
       " 'dotted lime bags contain 5 wavy cyan bags.',\n",
       " 'drab violet bags contain 4 dark beige bags, 1 plaid gold bag, 3 faded beige bags.',\n",
       " 'drab green bags contain 4 dotted bronze bags, 5 clear silver bags, 4 faded salmon bags.',\n",
       " 'wavy beige bags contain 2 clear cyan bags, 2 dim tomato bags.',\n",
       " 'wavy yellow bags contain 4 pale green bags, 3 mirrored green bags, 5 faded brown bags, 1 clear orange bag.',\n",
       " 'plaid tomato bags contain 3 dull yellow bags, 2 faded blue bags, 1 dull teal bag.',\n",
       " 'dull red bags contain 4 posh green bags, 1 shiny salmon bag, 2 bright tomato bags, 4 vibrant red bags.',\n",
       " 'striped salmon bags contain 4 dim bronze bags, 4 light gold bags, 3 posh beige bags.',\n",
       " 'dim crimson bags contain 1 dull crimson bag, 4 drab silver bags.',\n",
       " 'plaid silver bags contain 3 dull black bags, 5 shiny silver bags, 4 dark beige bags, 2 clear aqua bags.',\n",
       " 'clear bronze bags contain 1 drab coral bag, 2 vibrant red bags.',\n",
       " 'dotted gray bags contain 1 plaid plum bag, 2 dotted purple bags, 5 striped violet bags, 3 bright tomato bags.',\n",
       " 'striped silver bags contain 2 plaid coral bags, 5 bright orange bags, 1 pale brown bag.',\n",
       " 'shiny beige bags contain 4 dim turquoise bags.',\n",
       " 'posh green bags contain no other bags.',\n",
       " 'plaid gold bags contain 3 pale fuchsia bags, 5 dull lime bags, 5 wavy chartreuse bags, 5 dim tomato bags.',\n",
       " 'dim teal bags contain 5 pale beige bags, 2 faded blue bags, 5 dotted tan bags, 5 vibrant tomato bags.',\n",
       " 'bright red bags contain 4 drab lavender bags, 1 dark purple bag, 2 wavy violet bags.',\n",
       " 'dotted teal bags contain 5 dull crimson bags.',\n",
       " 'faded gray bags contain 4 mirrored red bags.',\n",
       " 'pale purple bags contain 3 faded gray bags, 1 clear gold bag, 4 clear cyan bags.',\n",
       " 'striped crimson bags contain 4 dim aqua bags, 3 pale magenta bags, 1 drab white bag, 1 vibrant purple bag.',\n",
       " 'mirrored purple bags contain 3 muted gray bags.',\n",
       " 'muted maroon bags contain 3 plaid crimson bags, 4 posh aqua bags.',\n",
       " 'muted gold bags contain 3 pale fuchsia bags, 2 dotted teal bags, 3 dotted chartreuse bags, 4 vibrant lime bags.',\n",
       " 'wavy silver bags contain 2 plaid beige bags, 3 dull aqua bags, 2 pale lavender bags.',\n",
       " 'dim aqua bags contain 5 bright beige bags.',\n",
       " 'dark tan bags contain 4 pale gold bags.',\n",
       " 'light yellow bags contain 4 dotted gray bags, 5 pale teal bags.',\n",
       " 'bright blue bags contain 3 shiny coral bags, 4 striped salmon bags.',\n",
       " 'striped cyan bags contain 5 light turquoise bags.',\n",
       " 'light gray bags contain 4 vibrant teal bags, 1 shiny turquoise bag, 1 wavy olive bag, 5 dim white bags.',\n",
       " 'light cyan bags contain 3 dark gray bags, 5 clear lavender bags, 4 dark beige bags.',\n",
       " 'light blue bags contain 5 dim black bags, 4 drab tomato bags, 2 dim turquoise bags.',\n",
       " 'dull crimson bags contain 3 pale silver bags, 2 faded beige bags.',\n",
       " 'dotted beige bags contain 2 dotted aqua bags.',\n",
       " 'shiny olive bags contain 4 bright plum bags, 4 clear plum bags, 2 wavy green bags, 5 faded tomato bags.',\n",
       " 'striped turquoise bags contain 1 drab black bag.',\n",
       " 'pale chartreuse bags contain 5 dotted brown bags.',\n",
       " 'mirrored turquoise bags contain 4 shiny gold bags, 3 dark chartreuse bags.',\n",
       " 'posh beige bags contain 3 dotted tan bags.',\n",
       " 'drab gray bags contain 3 vibrant aqua bags.',\n",
       " 'shiny silver bags contain 4 plaid gold bags, 5 shiny green bags.',\n",
       " 'bright crimson bags contain 5 faded yellow bags, 4 bright plum bags, 4 mirrored gold bags.',\n",
       " 'dim yellow bags contain 2 plaid lime bags, 5 bright salmon bags, 4 mirrored bronze bags.',\n",
       " 'dark crimson bags contain 4 dull blue bags, 2 light olive bags, 4 mirrored green bags.',\n",
       " 'faded aqua bags contain 1 dotted chartreuse bag, 1 muted orange bag.',\n",
       " 'pale turquoise bags contain 4 dull silver bags.',\n",
       " 'clear orange bags contain 1 pale gray bag, 5 striped bronze bags, 5 dim aqua bags.',\n",
       " 'mirrored red bags contain 1 muted purple bag.',\n",
       " 'drab silver bags contain no other bags.',\n",
       " 'faded silver bags contain 5 mirrored turquoise bags, 4 striped purple bags.',\n",
       " 'wavy fuchsia bags contain 2 faded purple bags, 1 wavy cyan bag, 2 muted cyan bags.',\n",
       " 'clear black bags contain 4 drab turquoise bags, 1 plaid lime bag.',\n",
       " 'dim olive bags contain 5 bright chartreuse bags, 3 striped silver bags.',\n",
       " 'mirrored tan bags contain 2 striped indigo bags, 3 wavy gray bags, 3 clear tan bags.',\n",
       " 'mirrored yellow bags contain 2 plaid plum bags, 3 striped salmon bags, 4 dim maroon bags.',\n",
       " 'shiny salmon bags contain 5 dotted plum bags, 5 pale crimson bags.',\n",
       " 'dotted crimson bags contain 3 dull yellow bags.',\n",
       " 'shiny fuchsia bags contain 5 plaid lime bags.',\n",
       " 'drab turquoise bags contain 2 dull crimson bags.',\n",
       " 'mirrored cyan bags contain 3 posh green bags, 5 striped olive bags, 5 vibrant red bags.',\n",
       " 'faded crimson bags contain 3 muted silver bags, 4 shiny olive bags.',\n",
       " 'light magenta bags contain 3 posh crimson bags, 5 pale purple bags.',\n",
       " 'faded violet bags contain 3 vibrant lime bags, 1 dim magenta bag, 1 dull lime bag.',\n",
       " 'dotted black bags contain 2 light gold bags, 2 dim bronze bags, 4 wavy turquoise bags.',\n",
       " 'bright beige bags contain 4 vibrant orange bags, 4 dark chartreuse bags, 1 muted gray bag, 2 bright tomato bags.',\n",
       " 'striped green bags contain 3 pale beige bags, 1 pale brown bag, 2 posh brown bags, 5 striped olive bags.',\n",
       " 'dotted red bags contain 4 vibrant orange bags, 2 pale gold bags.',\n",
       " 'plaid fuchsia bags contain 5 pale teal bags, 5 pale fuchsia bags, 4 faded gray bags.',\n",
       " 'light beige bags contain 1 muted red bag, 5 dotted purple bags, 3 striped salmon bags.',\n",
       " 'dim chartreuse bags contain 5 muted maroon bags, 4 wavy maroon bags.',\n",
       " 'clear chartreuse bags contain 3 striped lavender bags, 2 clear blue bags.',\n",
       " 'pale silver bags contain 2 dark teal bags.',\n",
       " 'faded olive bags contain 4 dotted turquoise bags, 4 drab indigo bags, 5 drab violet bags, 3 shiny blue bags.',\n",
       " 'clear blue bags contain 1 muted black bag.',\n",
       " 'dull tan bags contain 5 clear crimson bags, 3 dim tomato bags.',\n",
       " 'dark cyan bags contain 4 wavy magenta bags, 5 vibrant olive bags, 2 posh gray bags, 5 dull magenta bags.',\n",
       " 'dotted white bags contain 1 bright magenta bag, 3 pale red bags.',\n",
       " 'muted teal bags contain 5 posh fuchsia bags, 4 drab turquoise bags, 4 posh red bags.',\n",
       " 'mirrored coral bags contain 1 faded purple bag, 2 bright magenta bags, 5 dark yellow bags, 3 light plum bags.',\n",
       " 'dull orange bags contain 4 dotted blue bags, 5 clear gray bags, 3 vibrant red bags.',\n",
       " 'bright aqua bags contain 4 muted lime bags, 2 wavy plum bags, 1 shiny olive bag.',\n",
       " 'light maroon bags contain 1 shiny gold bag, 4 light beige bags, 1 drab black bag.',\n",
       " 'dim green bags contain 4 dull brown bags.',\n",
       " 'striped black bags contain 4 dotted crimson bags.',\n",
       " 'mirrored bronze bags contain 4 mirrored chartreuse bags, 3 dull lime bags, 3 wavy turquoise bags.',\n",
       " 'striped aqua bags contain 4 dark gray bags, 5 faded beige bags, 2 dull lime bags.',\n",
       " 'shiny coral bags contain 5 mirrored white bags, 5 shiny blue bags.',\n",
       " 'striped orange bags contain 4 pale silver bags, 4 pale olive bags, 4 shiny olive bags, 2 bright chartreuse bags.',\n",
       " 'vibrant crimson bags contain 5 shiny olive bags, 5 striped violet bags, 2 posh beige bags.',\n",
       " 'dotted chartreuse bags contain 5 bright turquoise bags, 5 bright magenta bags.',\n",
       " 'vibrant purple bags contain 4 posh violet bags.',\n",
       " 'vibrant violet bags contain 5 posh aqua bags, 4 mirrored white bags, 4 dotted tan bags, 4 mirrored purple bags.',\n",
       " 'dotted violet bags contain 3 bright brown bags, 3 pale yellow bags, 4 light gray bags, 5 dark green bags.',\n",
       " 'muted black bags contain 2 light violet bags, 5 muted bronze bags.',\n",
       " 'mirrored orange bags contain 1 plaid magenta bag, 5 muted red bags, 3 pale lime bags.',\n",
       " 'faded magenta bags contain 3 striped cyan bags, 4 muted silver bags.',\n",
       " 'clear gray bags contain 4 muted gray bags, 2 wavy turquoise bags, 3 dotted plum bags.']"
      ]
     },
     "execution_count": 812,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 813,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['vibrant', 'salmon', 'bags', 'contain', '1', 'vibrant', 'gold', 'bag,', '2', 'wavy', 'aqua', 'bags,', '1', 'dotted', 'crimson', 'bag.']\n",
      "['dotted', 'plum', 'bags', 'contain', '3', 'wavy', 'cyan', 'bags.']\n",
      "['muted', 'salmon', 'bags', 'contain', '2', 'pale', 'purple', 'bags,', '3', 'dull', 'orange', 'bags,', '2', 'dotted', 'lime', 'bags,', '3', 'clear', 'crimson', 'bags.']\n",
      "['wavy', 'green', 'bags', 'contain', '1', 'plaid', 'crimson', 'bag.']\n",
      "['light', 'salmon', 'bags', 'contain', '3', 'posh', 'lime', 'bags,', '1', 'plaid', 'plum', 'bag,', '3', 'faded', 'yellow', 'bags,', '4', 'clear', 'fuchsia', 'bags.']\n",
      "['dim', 'violet', 'bags', 'contain', '4', 'drab', 'tan', 'bags,', '4', 'drab', 'violet', 'bags,', '2', 'faded', 'coral', 'bags,', '4', 'dark', 'white', 'bags.']\n",
      "['dim', 'black', 'bags', 'contain', '4', 'posh', 'lime', 'bags.']\n",
      "['drab', 'indigo', 'bags', 'contain', '4', 'light', 'aqua', 'bags,', '2', 'light', 'white', 'bags,', '4', 'clear', 'plum', 'bags.']\n",
      "['clear', 'purple', 'bags', 'contain', '4', 'drab', 'olive', 'bags,', '2', 'vibrant', 'chartreuse', 'bags.']\n",
      "['wavy', 'indigo', 'bags', 'contain', '3', 'clear', 'maroon', 'bags,', '4', 'striped', 'blue', 'bags,', '2', 'wavy', 'gray', 'bags,', '2', 'dim', 'magenta', 'bags.']\n",
      "['drab', 'olive', 'bags', 'contain', '2', 'shiny', 'salmon', 'bags,', '4', 'mirrored', 'white', 'bags,', '4', 'mirrored', 'fuchsia', 'bags.']\n",
      "['plaid', 'crimson', 'bags', 'contain', '2', 'dull', 'chartreuse', 'bags,', '4', 'striped', 'maroon', 'bags,', '4', 'dull', 'crimson', 'bags,', '4', 'plaid', 'red', 'bags.']\n",
      "['pale', 'lavender', 'bags', 'contain', '4', 'dotted', 'tan', 'bags,', '5', 'striped', 'olive', 'bags.']\n",
      "['vibrant', 'maroon', 'bags', 'contain', '2', 'faded', 'plum', 'bags,', '4', 'wavy', 'aqua', 'bags,', '5', 'drab', 'lavender', 'bags,', '4', 'light', 'lavender', 'bags.']\n",
      "['wavy', 'coral', 'bags', 'contain', '5', 'drab', 'purple', 'bags.']\n",
      "['drab', 'salmon', 'bags', 'contain', '4', 'shiny', 'tan', 'bags,', '2', 'shiny', 'white', 'bags.']\n",
      "['light', 'green', 'bags', 'contain', '5', 'dim', 'turquoise', 'bags,', '4', 'striped', 'crimson', 'bags,', '5', 'dim', 'salmon', 'bags,', '3', 'clear', 'gray', 'bags.']\n",
      "['dark', 'indigo', 'bags', 'contain', '5', 'shiny', 'crimson', 'bags.']\n",
      "['dark', 'blue', 'bags', 'contain', '3', 'drab', 'indigo', 'bags,', '2', 'shiny', 'beige', 'bags,', '2', 'shiny', 'coral', 'bags.']\n",
      "['shiny', 'cyan', 'bags', 'contain', '2', 'striped', 'aqua', 'bags,', '2', 'drab', 'turquoise', 'bags,', '5', 'light', 'purple', 'bags.']\n",
      "['pale', 'cyan', 'bags', 'contain', '2', 'muted', 'violet', 'bags,', '2', 'clear', 'beige', 'bags,', '1', 'clear', 'indigo', 'bag,', '5', 'striped', 'turquoise', 'bags.']\n",
      "['muted', 'lime', 'bags', 'contain', '5', 'drab', 'silver', 'bags.']\n",
      "['shiny', 'brown', 'bags', 'contain', '4', 'clear', 'purple', 'bags,', '5', 'striped', 'chartreuse', 'bags,', '5', 'pale', 'lavender', 'bags.']\n",
      "['muted', 'purple', 'bags', 'contain', '4', 'dark', 'purple', 'bags,', '2', 'dull', 'crimson', 'bags.']\n",
      "['plaid', 'turquoise', 'bags', 'contain', '2', 'clear', 'gray', 'bags,', '4', 'clear', 'magenta', 'bags,', '4', 'dull', 'bronze', 'bags.']\n",
      "['clear', 'cyan', 'bags', 'contain', '3', 'dotted', 'plum', 'bags,', '3', 'shiny', 'coral', 'bags.']\n",
      "['shiny', 'violet', 'bags', 'contain', '3', 'drab', 'chartreuse', 'bags,', '1', 'pale', 'aqua', 'bag,', '3', 'bright', 'aqua', 'bags.']\n",
      "['wavy', 'tan', 'bags', 'contain', '5', 'dark', 'magenta', 'bags,', '4', 'dull', 'beige', 'bags,', '1', 'wavy', 'cyan', 'bag.']\n",
      "['mirrored', 'lime', 'bags', 'contain', '2', 'clear', 'plum', 'bags,', '3', 'dark', 'bronze', 'bags,', '5', 'faded', 'turquoise', 'bags,', '5', 'plaid', 'crimson', 'bags.']\n",
      "['wavy', 'purple', 'bags', 'contain', '3', 'dark', 'bronze', 'bags,', '2', 'bright', 'bronze', 'bags.']\n",
      "['plaid', 'plum', 'bags', 'contain', '5', 'muted', 'tan', 'bags,', '1', 'drab', 'teal', 'bag,', '2', 'dark', 'purple', 'bags,', '1', 'dotted', 'blue', 'bag.']\n",
      "['dotted', 'cyan', 'bags', 'contain', '4', 'vibrant', 'fuchsia', 'bags,', '3', 'muted', 'plum', 'bags.']\n",
      "['striped', 'white', 'bags', 'contain', '3', 'faded', 'salmon', 'bags,', '4', 'plaid', 'cyan', 'bags,', '5', 'wavy', 'gray', 'bags.']\n",
      "['posh', 'black', 'bags', 'contain', '2', 'dotted', 'blue', 'bags,', '3', 'muted', 'crimson', 'bags.']\n",
      "['dotted', 'bronze', 'bags', 'contain', '2', 'posh', 'tan', 'bags.']\n",
      "['muted', 'gray', 'bags', 'contain', '2', 'posh', 'green', 'bags.']\n",
      "['plaid', 'violet', 'bags', 'contain', '4', 'muted', 'orange', 'bags.']\n",
      "['muted', 'green', 'bags', 'contain', '3', 'drab', 'silver', 'bags,', '2', 'mirrored', 'maroon', 'bags,', '3', 'dark', 'teal', 'bags.']\n",
      "['dotted', 'tan', 'bags', 'contain', '3', 'pale', 'black', 'bags.']\n",
      "['dim', 'beige', 'bags', 'contain', '4', 'light', 'plum', 'bags,', '4', 'posh', 'blue', 'bags,', '4', 'dotted', 'purple', 'bags.']\n",
      "['posh', 'magenta', 'bags', 'contain', '2', 'clear', 'purple', 'bags,', '4', 'posh', 'aqua', 'bags.']\n",
      "['bright', 'coral', 'bags', 'contain', '5', 'light', 'bronze', 'bags,', '2', 'vibrant', 'crimson', 'bags,', '4', 'dark', 'gold', 'bags.']\n",
      "['pale', 'bronze', 'bags', 'contain', '1', 'striped', 'orange', 'bag.']\n",
      "['dim', 'lime', 'bags', 'contain', '3', 'dim', 'green', 'bags.']\n",
      "['plaid', 'green', 'bags', 'contain', '2', 'faded', 'brown', 'bags,', '3', 'faded', 'bronze', 'bags,', '3', 'pale', 'green', 'bags,', '5', 'plaid', 'magenta', 'bags.']\n",
      "['vibrant', 'cyan', 'bags', 'contain', '5', 'pale', 'black', 'bags,', '5', 'vibrant', 'violet', 'bags,', '1', 'mirrored', 'red', 'bag.']\n",
      "['dotted', 'fuchsia', 'bags', 'contain', '3', 'dull', 'crimson', 'bags,', '2', 'wavy', 'silver', 'bags,', '4', 'muted', 'purple', 'bags.']\n",
      "['dim', 'red', 'bags', 'contain', '2', 'clear', 'indigo', 'bags,', '5', 'dotted', 'yellow', 'bags.']\n",
      "['faded', 'black', 'bags', 'contain', '4', 'bright', 'fuchsia', 'bags.']\n",
      "['faded', 'chartreuse', 'bags', 'contain', '4', 'striped', 'orange', 'bags.']\n",
      "['plaid', 'blue', 'bags', 'contain', '5', 'dim', 'gray', 'bags,', '2', 'pale', 'salmon', 'bags,', '2', 'muted', 'orange', 'bags.']\n",
      "['plaid', 'teal', 'bags', 'contain', '5', 'bright', 'lavender', 'bags.']\n",
      "['drab', 'magenta', 'bags', 'contain', '2', 'dim', 'crimson', 'bags,', '1', 'bright', 'fuchsia', 'bag.']\n",
      "['clear', 'violet', 'bags', 'contain', '3', 'mirrored', 'white', 'bags,', '5', 'faded', 'lime', 'bags,', '2', 'light', 'olive', 'bags,', '1', 'dotted', 'turquoise', 'bag.']\n",
      "['posh', 'tan', 'bags', 'contain', '3', 'posh', 'orange', 'bags,', '1', 'vibrant', 'purple', 'bag,', '4', 'posh', 'gray', 'bags,', '2', 'mirrored', 'fuchsia', 'bags.']\n",
      "['posh', 'red', 'bags', 'contain', '5', 'mirrored', 'red', 'bags.']\n",
      "['striped', 'lavender', 'bags', 'contain', '5', 'dotted', 'crimson', 'bags,', '1', 'dotted', 'purple', 'bag.']\n",
      "['dull', 'salmon', 'bags', 'contain', '1', 'wavy', 'black', 'bag,', '2', 'dull', 'lime', 'bags,', '3', 'bright', 'plum', 'bags,', '2', 'dark', 'gray', 'bags.']\n",
      "['light', 'tan', 'bags', 'contain', '3', 'wavy', 'violet', 'bags,', '1', 'shiny', 'olive', 'bag,', '5', 'bright', 'brown', 'bags.']\n",
      "['pale', 'orange', 'bags', 'contain', '5', 'vibrant', 'orange', 'bags,', '3', 'wavy', 'black', 'bags.']\n",
      "['mirrored', 'green', 'bags', 'contain', '1', 'dark', 'tan', 'bag.']\n",
      "['plaid', 'gray', 'bags', 'contain', '4', 'muted', 'magenta', 'bags.']\n",
      "['dim', 'maroon', 'bags', 'contain', '3', 'light', 'magenta', 'bags,', '4', 'dull', 'red', 'bags.']\n",
      "['dull', 'cyan', 'bags', 'contain', '1', 'wavy', 'blue', 'bag,', '1', 'dark', 'chartreuse', 'bag.']\n",
      "['mirrored', 'blue', 'bags', 'contain', '4', 'dark', 'cyan', 'bags,', '4', 'muted', 'magenta', 'bags,', '2', 'striped', 'olive', 'bags,', '1', 'posh', 'gold', 'bag.']\n",
      "['plaid', 'purple', 'bags', 'contain', '1', 'shiny', 'orange', 'bag,', '5', 'plaid', 'coral', 'bags,', '4', 'dim', 'red', 'bags,', '5', 'faded', 'aqua', 'bags.']\n",
      "['vibrant', 'magenta', 'bags', 'contain', '5', 'posh', 'aqua', 'bags,', '5', 'shiny', 'chartreuse', 'bags,', '4', 'dark', 'teal', 'bags.']\n",
      "['bright', 'indigo', 'bags', 'contain', '1', 'dark', 'bronze', 'bag.']\n",
      "['bright', 'yellow', 'bags', 'contain', '4', 'muted', 'lime', 'bags,', '1', 'drab', 'maroon', 'bag.']\n",
      "['clear', 'gold', 'bags', 'contain', '2', 'striped', 'blue', 'bags,', '3', 'clear', 'green', 'bags,', '4', 'drab', 'indigo', 'bags.']\n",
      "['wavy', 'red', 'bags', 'contain', '5', 'faded', 'fuchsia', 'bags,', '5', 'mirrored', 'indigo', 'bags.']\n",
      "['dark', 'coral', 'bags', 'contain', '3', 'drab', 'aqua', 'bags,', '5', 'bright', 'fuchsia', 'bags.']\n",
      "['striped', 'teal', 'bags', 'contain', '1', 'clear', 'red', 'bag,', '3', 'drab', 'magenta', 'bags,', '4', 'dim', 'green', 'bags,', '2', 'dark', 'fuchsia', 'bags.']\n",
      "['pale', 'salmon', 'bags', 'contain', '1', 'muted', 'gray', 'bag,', '4', 'dotted', 'lavender', 'bags,', '3', 'dark', 'maroon', 'bags,', '4', 'plaid', 'plum', 'bags.']\n",
      "['dull', 'plum', 'bags', 'contain', '3', 'dim', 'black', 'bags,', '5', 'shiny', 'aqua', 'bags,', '3', 'pale', 'teal', 'bags,', '4', 'clear', 'purple', 'bags.']\n",
      "['plaid', 'indigo', 'bags', 'contain', '4', 'drab', 'maroon', 'bags,', '2', 'shiny', 'chartreuse', 'bags,', '4', 'shiny', 'yellow', 'bags,', '1', 'pale', 'violet', 'bag.']\n",
      "['shiny', 'orange', 'bags', 'contain', '5', 'bright', 'silver', 'bags,', '2', 'light', 'olive', 'bags,', '5', 'light', 'beige', 'bags.']\n",
      "['dotted', 'salmon', 'bags', 'contain', '4', 'posh', 'chartreuse', 'bags,', '4', 'light', 'crimson', 'bags,', '5', 'muted', 'yellow', 'bags.']\n",
      "['vibrant', 'aqua', 'bags', 'contain', '2', 'dull', 'brown', 'bags.']\n",
      "['shiny', 'bronze', 'bags', 'contain', '1', 'mirrored', 'teal', 'bag,', '2', 'drab', 'tomato', 'bags.']\n",
      "['dark', 'black', 'bags', 'contain', '5', 'muted', 'red', 'bags,', '5', 'mirrored', 'crimson', 'bags.']\n",
      "['muted', 'bronze', 'bags', 'contain', '3', 'clear', 'tomato', 'bags,', '1', 'vibrant', 'purple', 'bag.']\n",
      "['faded', 'beige', 'bags', 'contain', '1', 'shiny', 'blue', 'bag,', '5', 'plaid', 'lime', 'bags.']\n",
      "['pale', 'green', 'bags', 'contain', '2', 'pale', 'crimson', 'bags,', '4', 'muted', 'cyan', 'bags.']\n",
      "['vibrant', 'bronze', 'bags', 'contain', '1', 'bright', 'lavender', 'bag.']\n",
      "['posh', 'salmon', 'bags', 'contain', '1', 'clear', 'green', 'bag,', '2', 'plaid', 'yellow', 'bags,', '3', 'bright', 'orange', 'bags.']\n",
      "['dull', 'yellow', 'bags', 'contain', '1', 'clear', 'plum', 'bag,', '2', 'dim', 'bronze', 'bags.']\n",
      "['mirrored', 'indigo', 'bags', 'contain', '5', 'dark', 'tomato', 'bags,', '5', 'pale', 'coral', 'bags,', '5', 'light', 'magenta', 'bags,', '5', 'striped', 'turquoise', 'bags.']\n",
      "['muted', 'chartreuse', 'bags', 'contain', '3', 'dark', 'tan', 'bags,', '4', 'dotted', 'teal', 'bags.']\n",
      "['drab', 'bronze', 'bags', 'contain', '3', 'pale', 'lavender', 'bags,', '1', 'bright', 'salmon', 'bag,', '4', 'plaid', 'red', 'bags.']\n",
      "['dim', 'cyan', 'bags', 'contain', '1', 'bright', 'plum', 'bag.']\n",
      "['drab', 'purple', 'bags', 'contain', '1', 'dim', 'fuchsia', 'bag,', '4', 'mirrored', 'turquoise', 'bags,', '5', 'striped', 'blue', 'bags.']\n",
      "['pale', 'violet', 'bags', 'contain', '5', 'posh', 'brown', 'bags,', '5', 'striped', 'plum', 'bags,', '1', 'dotted', 'indigo', 'bag.']\n",
      "['wavy', 'maroon', 'bags', 'contain', '3', 'shiny', 'blue', 'bags,', '3', 'wavy', 'cyan', 'bags,', '1', 'faded', 'purple', 'bag,', '4', 'posh', 'lime', 'bags.']\n",
      "['vibrant', 'coral', 'bags', 'contain', '3', 'shiny', 'turquoise', 'bags,', '4', 'mirrored', 'maroon', 'bags.']\n",
      "['vibrant', 'lavender', 'bags', 'contain', '2', 'drab', 'turquoise', 'bags,', '2', 'clear', 'red', 'bags.']\n",
      "['striped', 'fuchsia', 'bags', 'contain', '4', 'dotted', 'tan', 'bags,', '4', 'posh', 'silver', 'bags,', '4', 'clear', 'maroon', 'bags,', '5', 'wavy', 'fuchsia', 'bags.']\n",
      "['muted', 'lavender', 'bags', 'contain', '2', 'pale', 'aqua', 'bags,', '2', 'bright', 'green', 'bags,', '5', 'posh', 'beige', 'bags.']\n",
      "['posh', 'tomato', 'bags', 'contain', '2', 'vibrant', 'bronze', 'bags,', '3', 'light', 'brown', 'bags,', '5', 'posh', 'indigo', 'bags.']\n",
      "['dull', 'lavender', 'bags', 'contain', '2', 'wavy', 'olive', 'bags.']\n",
      "['mirrored', 'violet', 'bags', 'contain', '5', 'wavy', 'violet', 'bags,', '2', 'posh', 'cyan', 'bags,', '2', 'dull', 'olive', 'bags,', '3', 'drab', 'yellow', 'bags.']\n",
      "['mirrored', 'chartreuse', 'bags', 'contain', '2', 'shiny', 'salmon', 'bags,', '5', 'dark', 'purple', 'bags,', '2', 'posh', 'lime', 'bags.']\n",
      "['dim', 'brown', 'bags', 'contain', '4', 'clear', 'red', 'bags,', '1', 'drab', 'blue', 'bag,', '1', 'pale', 'silver', 'bag,', '5', 'dark', 'gray', 'bags.']\n",
      "['striped', 'magenta', 'bags', 'contain', '1', 'light', 'orange', 'bag,', '4', 'muted', 'beige', 'bags.']\n",
      "['light', 'red', 'bags', 'contain', '3', 'shiny', 'yellow', 'bags,', '3', 'faded', 'tan', 'bags,', '3', 'vibrant', 'lime', 'bags,', '3', 'muted', 'coral', 'bags.']\n",
      "['muted', 'olive', 'bags', 'contain', '4', 'drab', 'coral', 'bags,', '5', 'light', 'salmon', 'bags,', '1', 'vibrant', 'violet', 'bag.']\n",
      "['clear', 'silver', 'bags', 'contain', '1', 'posh', 'aqua', 'bag,', '1', 'drab', 'teal', 'bag,', '4', 'dark', 'orange', 'bags.']\n",
      "['faded', 'orange', 'bags', 'contain', '4', 'vibrant', 'purple', 'bags,', '4', 'wavy', 'cyan', 'bags,', '1', 'drab', 'brown', 'bag.']\n",
      "['mirrored', 'crimson', 'bags', 'contain', '5', 'light', 'aqua', 'bags,', '1', 'wavy', 'olive', 'bag,', '2', 'vibrant', 'lime', 'bags.']\n",
      "['shiny', 'plum', 'bags', 'contain', '2', 'shiny', 'maroon', 'bags,', '3', 'dark', 'red', 'bags.']\n",
      "['faded', 'green', 'bags', 'contain', '3', 'striped', 'turquoise', 'bags.']\n",
      "['bright', 'orange', 'bags', 'contain', '1', 'dull', 'crimson', 'bag,', '1', 'pale', 'lavender', 'bag,', '5', 'shiny', 'aqua', 'bags.']\n",
      "['dim', 'gray', 'bags', 'contain', '2', 'drab', 'indigo', 'bags,', '5', 'dim', 'turquoise', 'bags.']\n",
      "['mirrored', 'plum', 'bags', 'contain', '1', 'vibrant', 'red', 'bag,', '4', 'dotted', 'purple', 'bags.']\n",
      "['posh', 'gold', 'bags', 'contain', '4', 'bright', 'red', 'bags.']\n",
      "['posh', 'silver', 'bags', 'contain', '3', 'drab', 'coral', 'bags,', '1', 'faded', 'tan', 'bag,', '1', 'bright', 'silver', 'bag,', '1', 'shiny', 'blue', 'bag.']\n",
      "['dull', 'lime', 'bags', 'contain', '5', 'muted', 'tan', 'bags,', '4', 'mirrored', 'cyan', 'bags.']\n",
      "['faded', 'turquoise', 'bags', 'contain', '2', 'pale', 'teal', 'bags,', '2', 'bright', 'green', 'bags.']\n",
      "['bright', 'salmon', 'bags', 'contain', '1', 'dim', 'white', 'bag,', '2', 'clear', 'tomato', 'bags,', '1', 'bright', 'aqua', 'bag.']\n",
      "['dim', 'gold', 'bags', 'contain', '3', 'mirrored', 'turquoise', 'bags,', '5', 'wavy', 'tomato', 'bags.']\n",
      "['dull', 'fuchsia', 'bags', 'contain', '2', 'pale', 'beige', 'bags,', '1', 'dotted', 'yellow', 'bag.']\n",
      "['dark', 'beige', 'bags', 'contain', '2', 'pale', 'magenta', 'bags.']\n",
      "['dotted', 'maroon', 'bags', 'contain', '2', 'dark', 'tomato', 'bags,', '2', 'light', 'gray', 'bags,', '3', 'faded', 'teal', 'bags,', '1', 'clear', 'gray', 'bag.']\n",
      "['muted', 'white', 'bags', 'contain', '3', 'dull', 'turquoise', 'bags,', '5', 'dark', 'bronze', 'bags,', '1', 'light', 'olive', 'bag,', '3', 'clear', 'bronze', 'bags.']\n",
      "['faded', 'blue', 'bags', 'contain', '1', 'dark', 'chartreuse', 'bag,', '3', 'pale', 'aqua', 'bags,', '5', 'faded', 'crimson', 'bags.']\n",
      "['clear', 'aqua', 'bags', 'contain', '3', 'vibrant', 'olive', 'bags,', '5', 'clear', 'crimson', 'bags.']\n",
      "['faded', 'cyan', 'bags', 'contain', '1', 'vibrant', 'blue', 'bag,', '1', 'light', 'magenta', 'bag.']\n",
      "['shiny', 'aqua', 'bags', 'contain', '1', 'clear', 'green', 'bag.']\n",
      "['bright', 'gray', 'bags', 'contain', '2', 'dim', 'fuchsia', 'bags,', '1', 'striped', 'chartreuse', 'bag,', '2', 'clear', 'aqua', 'bags,', '2', 'dull', 'olive', 'bags.']\n",
      "['bright', 'white', 'bags', 'contain', '2', 'light', 'purple', 'bags,', '5', 'bright', 'aqua', 'bags.']\n",
      "['bright', 'lime', 'bags', 'contain', '1', 'pale', 'orange', 'bag,', '5', 'plaid', 'magenta', 'bags,', '4', 'mirrored', 'maroon', 'bags.']\n",
      "['dark', 'lavender', 'bags', 'contain', '5', 'mirrored', 'bronze', 'bags,', '4', 'dotted', 'aqua', 'bags.']\n",
      "['striped', 'chartreuse', 'bags', 'contain', '3', 'striped', 'indigo', 'bags,', '2', 'faded', 'plum', 'bags,', '4', 'clear', 'gray', 'bags.']\n",
      "['muted', 'magenta', 'bags', 'contain', '3', 'clear', 'red', 'bags,', '3', 'dull', 'crimson', 'bags,', '1', 'clear', 'aqua', 'bag,', '4', 'faded', 'tomato', 'bags.']\n",
      "['clear', 'magenta', 'bags', 'contain', '2', 'striped', 'cyan', 'bags,', '5', 'vibrant', 'lime', 'bags,', '4', 'striped', 'salmon', 'bags.']\n",
      "['pale', 'yellow', 'bags', 'contain', '3', 'faded', 'fuchsia', 'bags,', '2', 'dotted', 'lime', 'bags,', '5', 'pale', 'gold', 'bags,', '1', 'plaid', 'tomato', 'bag.']\n",
      "['dull', 'teal', 'bags', 'contain', '4', 'dim', 'green', 'bags,', '1', 'drab', 'maroon', 'bag,', '2', 'dim', 'crimson', 'bags.']\n",
      "['pale', 'brown', 'bags', 'contain', '5', 'drab', 'orange', 'bags,', '2', 'dotted', 'purple', 'bags,', '3', 'plaid', 'olive', 'bags,', '3', 'pale', 'black', 'bags.']\n",
      "['posh', 'blue', 'bags', 'contain', '4', 'faded', 'purple', 'bags,', '4', 'drab', 'turquoise', 'bags.']\n",
      "['pale', 'olive', 'bags', 'contain', '5', 'muted', 'silver', 'bags,', '3', 'mirrored', 'plum', 'bags,', '4', 'vibrant', 'lime', 'bags,', '5', 'striped', 'olive', 'bags.']\n",
      "['plaid', 'black', 'bags', 'contain', '3', 'posh', 'yellow', 'bags.']\n",
      "['striped', 'tomato', 'bags', 'contain', '4', 'faded', 'blue', 'bags,', '2', 'shiny', 'magenta', 'bags.']\n",
      "['wavy', 'tomato', 'bags', 'contain', '1', 'pale', 'gold', 'bag,', '2', 'dim', 'magenta', 'bags.']\n",
      "['faded', 'plum', 'bags', 'contain', '3', 'light', 'violet', 'bags,', '3', 'posh', 'beige', 'bags,', '3', 'striped', 'aqua', 'bags,', '4', 'dim', 'magenta', 'bags.']\n",
      "['vibrant', 'turquoise', 'bags', 'contain', '3', 'muted', 'silver', 'bags,', '5', 'dotted', 'black', 'bags.']\n",
      "['dull', 'white', 'bags', 'contain', '5', 'dim', 'gray', 'bags,', '1', 'faded', 'crimson', 'bag.']\n",
      "['faded', 'purple', 'bags', 'contain', '1', 'vibrant', 'orange', 'bag,', '4', 'pale', 'crimson', 'bags,', '5', 'shiny', 'blue', 'bags,', '1', 'light', 'gold', 'bag.']\n",
      "['clear', 'white', 'bags', 'contain', '1', 'striped', 'orange', 'bag,', '3', 'pale', 'coral', 'bags,', '5', 'plaid', 'chartreuse', 'bags.']\n",
      "['striped', 'maroon', 'bags', 'contain', '2', 'wavy', 'olive', 'bags.']\n",
      "['light', 'tomato', 'bags', 'contain', '2', 'pale', 'crimson', 'bags,', '3', 'bright', 'fuchsia', 'bags,', '2', 'pale', 'salmon', 'bags,', '3', 'pale', 'olive', 'bags.']\n",
      "['drab', 'tomato', 'bags', 'contain', '1', 'pale', 'olive', 'bag.']\n",
      "['dark', 'aqua', 'bags', 'contain', '1', 'shiny', 'magenta', 'bag,', '4', 'faded', 'lime', 'bags,', '4', 'faded', 'gold', 'bags.']\n",
      "['plaid', 'bronze', 'bags', 'contain', '2', 'pale', 'purple', 'bags.']\n",
      "['dark', 'plum', 'bags', 'contain', '3', 'wavy', 'brown', 'bags,', '1', 'bright', 'salmon', 'bag.']\n",
      "['dark', 'purple', 'bags', 'contain', '4', 'dotted', 'red', 'bags.']\n",
      "['light', 'teal', 'bags', 'contain', '1', 'vibrant', 'indigo', 'bag,', '5', 'wavy', 'olive', 'bags,', '4', 'clear', 'maroon', 'bags,', '1', 'light', 'silver', 'bag.']\n",
      "['drab', 'fuchsia', 'bags', 'contain', '3', 'faded', 'turquoise', 'bags,', '5', 'dim', 'yellow', 'bags.']\n",
      "['light', 'turquoise', 'bags', 'contain', '1', 'dotted', 'blue', 'bag,', '4', 'mirrored', 'tomato', 'bags.']\n",
      "['clear', 'maroon', 'bags', 'contain', '4', 'mirrored', 'green', 'bags.']\n",
      "['posh', 'maroon', 'bags', 'contain', '3', 'dim', 'black', 'bags,', '3', 'bright', 'gold', 'bags,', '3', 'mirrored', 'white', 'bags,', '1', 'clear', 'lavender', 'bag.']\n",
      "['dotted', 'blue', 'bags', 'contain', '2', 'wavy', 'maroon', 'bags.']\n",
      "['bright', 'tan', 'bags', 'contain', '4', 'faded', 'turquoise', 'bags,', '5', 'drab', 'coral', 'bags,', '5', 'dull', 'red', 'bags,', '2', 'dim', 'gray', 'bags.']\n",
      "['dark', 'salmon', 'bags', 'contain', '4', 'clear', 'fuchsia', 'bags,', '5', 'mirrored', 'red', 'bags.']\n",
      "['mirrored', 'fuchsia', 'bags', 'contain', '4', 'bright', 'tomato', 'bags,', '3', 'vibrant', 'orange', 'bags.']\n",
      "['vibrant', 'green', 'bags', 'contain', '1', 'clear', 'lavender', 'bag.']\n",
      "['dim', 'white', 'bags', 'contain', '5', 'dull', 'red', 'bags.']\n",
      "['light', 'white', 'bags', 'contain', '3', 'dark', 'purple', 'bags,', '1', 'mirrored', 'fuchsia', 'bag,', '1', 'plaid', 'gold', 'bag,', '1', 'posh', 'lime', 'bag.']\n",
      "['dark', 'turquoise', 'bags', 'contain', '3', 'striped', 'green', 'bags,', '1', 'dull', 'gold', 'bag,', '2', 'pale', 'gray', 'bags.']\n",
      "['light', 'purple', 'bags', 'contain', '5', 'muted', 'brown', 'bags,', '5', 'muted', 'purple', 'bags,', '4', 'dull', 'yellow', 'bags,', '5', 'vibrant', 'gold', 'bags.']\n",
      "['posh', 'lavender', 'bags', 'contain', '5', 'posh', 'yellow', 'bags,', '4', 'plaid', 'plum', 'bags,', '1', 'dark', 'fuchsia', 'bag,', '1', 'bright', 'maroon', 'bag.']\n",
      "['posh', 'crimson', 'bags', 'contain', '1', 'vibrant', 'gold', 'bag,', '5', 'clear', 'green', 'bags,', '2', 'posh', 'chartreuse', 'bags.']\n",
      "['wavy', 'lime', 'bags', 'contain', '5', 'mirrored', 'beige', 'bags.']\n",
      "['wavy', 'black', 'bags', 'contain', '1', 'plaid', 'orange', 'bag,', '4', 'shiny', 'green', 'bags,', '3', 'shiny', 'blue', 'bags,', '4', 'muted', 'red', 'bags.']\n",
      "['muted', 'red', 'bags', 'contain', '4', 'vibrant', 'lime', 'bags,', '2', 'drab', 'black', 'bags,', '4', 'vibrant', 'red', 'bags,', '5', 'faded', 'beige', 'bags.']\n",
      "['vibrant', 'gold', 'bags', 'contain', '2', 'bright', 'silver', 'bags,', '4', 'faded', 'teal', 'bags,', '2', 'vibrant', 'orange', 'bags,', '3', 'striped', 'salmon', 'bags.']\n",
      "['shiny', 'crimson', 'bags', 'contain', '2', 'bright', 'yellow', 'bags.']\n",
      "['muted', 'turquoise', 'bags', 'contain', '5', 'bright', 'plum', 'bags.']\n",
      "['posh', 'orange', 'bags', 'contain', '4', 'vibrant', 'yellow', 'bags,', '5', 'clear', 'crimson', 'bags.']\n",
      "['wavy', 'aqua', 'bags', 'contain', '5', 'shiny', 'green', 'bags,', '5', 'bright', 'fuchsia', 'bags,', '4', 'muted', 'fuchsia', 'bags.']\n",
      "['clear', 'green', 'bags', 'contain', '4', 'dotted', 'plum', 'bags,', '2', 'vibrant', 'olive', 'bags,', '5', 'pale', 'beige', 'bags.']\n",
      "['pale', 'aqua', 'bags', 'contain', '3', 'dark', 'tomato', 'bags,', '5', 'posh', 'lime', 'bags.']\n",
      "['drab', 'maroon', 'bags', 'contain', '5', 'bright', 'magenta', 'bags,', '2', 'bright', 'plum', 'bags,', '5', 'clear', 'green', 'bags,', '3', 'faded', 'tomato', 'bags.']\n",
      "['vibrant', 'plum', 'bags', 'contain', '3', 'light', 'crimson', 'bags,', '5', 'dotted', 'silver', 'bags,', '5', 'mirrored', 'red', 'bags,', '1', 'dotted', 'turquoise', 'bag.']\n",
      "['posh', 'yellow', 'bags', 'contain', '5', 'plaid', 'lavender', 'bags,', '5', 'dim', 'tomato', 'bags.']\n",
      "['faded', 'brown', 'bags', 'contain', '1', 'striped', 'orange', 'bag,', '5', 'wavy', 'green', 'bags.']\n",
      "['drab', 'cyan', 'bags', 'contain', '4', 'faded', 'teal', 'bags,', '3', 'vibrant', 'aqua', 'bags,', '2', 'light', 'chartreuse', 'bags,', '3', 'dark', 'orange', 'bags.']\n",
      "['dark', 'lime', 'bags', 'contain', '4', 'vibrant', 'blue', 'bags.']\n",
      "['faded', 'coral', 'bags', 'contain', '4', 'wavy', 'green', 'bags,', '4', 'mirrored', 'gold', 'bags,', '3', 'striped', 'fuchsia', 'bags,', '1', 'pale', 'fuchsia', 'bag.']\n",
      "['dark', 'orange', 'bags', 'contain', '1', 'dotted', 'red', 'bag,', '2', 'vibrant', 'red', 'bags.']\n",
      "['wavy', 'magenta', 'bags', 'contain', '3', 'dull', 'chartreuse', 'bags,', '2', 'dim', 'maroon', 'bags,', '2', 'clear', 'maroon', 'bags.']\n",
      "['plaid', 'coral', 'bags', 'contain', '4', 'drab', 'tan', 'bags,', '1', 'pale', 'tan', 'bag.']\n",
      "['mirrored', 'salmon', 'bags', 'contain', '1', 'muted', 'bronze', 'bag,', '5', 'muted', 'purple', 'bags.']\n",
      "['dim', 'tomato', 'bags', 'contain', '2', 'drab', 'silver', 'bags,', '4', 'mirrored', 'purple', 'bags,', '1', 'dull', 'olive', 'bag,', '5', 'dotted', 'purple', 'bags.']\n",
      "['wavy', 'gold', 'bags', 'contain', '3', 'dark', 'crimson', 'bags,', '1', 'dim', 'white', 'bag.']\n",
      "['light', 'fuchsia', 'bags', 'contain', '3', 'mirrored', 'green', 'bags,', '2', 'wavy', 'fuchsia', 'bags.']\n",
      "['pale', 'tomato', 'bags', 'contain', '4', 'clear', 'purple', 'bags,', '5', 'faded', 'brown', 'bags,', '4', 'light', 'coral', 'bags.']\n",
      "['faded', 'yellow', 'bags', 'contain', '5', 'wavy', 'olive', 'bags,', '2', 'pale', 'lavender', 'bags,', '4', 'bright', 'plum', 'bags.']\n",
      "['light', 'violet', 'bags', 'contain', '1', 'dotted', 'red', 'bag,', '4', 'dim', 'aqua', 'bags.']\n",
      "['posh', 'lime', 'bags', 'contain', '2', 'pale', 'crimson', 'bags,', '1', 'pale', 'gold', 'bag,', '1', 'shiny', 'blue', 'bag,', '4', 'muted', 'gray', 'bags.']\n",
      "['mirrored', 'silver', 'bags', 'contain', '4', 'striped', 'bronze', 'bags,', '3', 'faded', 'salmon', 'bags,', '3', 'drab', 'green', 'bags,', '4', 'striped', 'green', 'bags.']\n",
      "['dark', 'green', 'bags', 'contain', '5', 'striped', 'maroon', 'bags,', '3', 'dim', 'olive', 'bags,', '4', 'vibrant', 'chartreuse', 'bags,', '5', 'dim', 'white', 'bags.']\n",
      "['mirrored', 'olive', 'bags', 'contain', '2', 'dotted', 'red', 'bags,', '5', 'dim', 'white', 'bags.']\n",
      "['dark', 'teal', 'bags', 'contain', '3', 'wavy', 'olive', 'bags,', '3', 'pale', 'crimson', 'bags.']\n",
      "['pale', 'tan', 'bags', 'contain', '2', 'dark', 'orange', 'bags,', '5', 'bright', 'plum', 'bags,', '4', 'pale', 'crimson', 'bags.']\n",
      "['wavy', 'plum', 'bags', 'contain', '3', 'dull', 'lime', 'bags.']\n",
      "['light', 'indigo', 'bags', 'contain', '5', 'dark', 'magenta', 'bags.']\n",
      "['drab', 'lime', 'bags', 'contain', '1', 'bright', 'fuchsia', 'bag,', '4', 'wavy', 'brown', 'bags.']\n",
      "['drab', 'tan', 'bags', 'contain', '3', 'bright', 'tomato', 'bags,', '1', 'muted', 'green', 'bag.']\n",
      "['vibrant', 'indigo', 'bags', 'contain', '5', 'dull', 'chartreuse', 'bags,', '5', 'clear', 'aqua', 'bags.']\n",
      "['dark', 'bronze', 'bags', 'contain', '3', 'dull', 'red', 'bags,', '3', 'mirrored', 'maroon', 'bags,', '1', 'muted', 'green', 'bag.']\n",
      "['shiny', 'red', 'bags', 'contain', '2', 'dark', 'bronze', 'bags,', '4', 'faded', 'magenta', 'bags,', '5', 'dull', 'teal', 'bags.']\n",
      "['shiny', 'black', 'bags', 'contain', '3', 'vibrant', 'olive', 'bags,', '2', 'plaid', 'lime', 'bags,', '5', 'shiny', 'gold', 'bags,', '2', 'dotted', 'plum', 'bags.']\n",
      "['light', 'gold', 'bags', 'contain', '5', 'vibrant', 'olive', 'bags.']\n",
      "['light', 'plum', 'bags', 'contain', '5', 'clear', 'gray', 'bags,', '5', 'dotted', 'chartreuse', 'bags,', '4', 'plaid', 'red', 'bags,', '1', 'plaid', 'lime', 'bag.']\n",
      "['bright', 'violet', 'bags', 'contain', '4', 'bright', 'maroon', 'bags,', '5', 'posh', 'red', 'bags,', '2', 'faded', 'olive', 'bags,', '4', 'dim', 'gray', 'bags.']\n",
      "['faded', 'red', 'bags', 'contain', '4', 'drab', 'maroon', 'bags,', '4', 'vibrant', 'violet', 'bags,', '1', 'faded', 'purple', 'bag,', '2', 'dotted', 'black', 'bags.']\n",
      "['muted', 'orange', 'bags', 'contain', '4', 'plaid', 'chartreuse', 'bags,', '5', 'muted', 'lavender', 'bags,', '2', 'faded', 'purple', 'bags.']\n",
      "['clear', 'coral', 'bags', 'contain', '2', 'drab', 'teal', 'bags,', '5', 'bright', 'turquoise', 'bags.']\n",
      "['wavy', 'orange', 'bags', 'contain', '4', 'muted', 'cyan', 'bags,', '3', 'light', 'indigo', 'bags,', '5', 'bright', 'black', 'bags,', '5', 'light', 'salmon', 'bags.']\n",
      "['faded', 'fuchsia', 'bags', 'contain', '3', 'pale', 'gold', 'bags,', '3', 'faded', 'salmon', 'bags,', '4', 'pale', 'red', 'bags.']\n",
      "['light', 'brown', 'bags', 'contain', '4', 'pale', 'silver', 'bags,', '4', 'clear', 'tan', 'bags.']\n",
      "['shiny', 'gray', 'bags', 'contain', '3', 'muted', 'teal', 'bags,', '1', 'bright', 'purple', 'bag,', '2', 'bright', 'olive', 'bags,', '4', 'mirrored', 'green', 'bags.']\n",
      "['bright', 'brown', 'bags', 'contain', '2', 'dark', 'teal', 'bags,', '5', 'light', 'plum', 'bags,', '2', 'plaid', 'olive', 'bags,', '5', 'dark', 'chartreuse', 'bags.']\n",
      "['mirrored', 'white', 'bags', 'contain', '1', 'wavy', 'gray', 'bag,', '3', 'bright', 'tomato', 'bags,', '1', 'muted', 'silver', 'bag,', '4', 'striped', 'olive', 'bags.']\n",
      "['pale', 'magenta', 'bags', 'contain', '1', 'clear', 'gray', 'bag,', '1', 'muted', 'gray', 'bag,', '1', 'wavy', 'cyan', 'bag,', '4', 'dull', 'brown', 'bags.']\n",
      "['bright', 'magenta', 'bags', 'contain', '2', 'muted', 'tan', 'bags,', '1', 'pale', 'gold', 'bag,', '2', 'wavy', 'cyan', 'bags,', '4', 'vibrant', 'orange', 'bags.']\n",
      "['clear', 'teal', 'bags', 'contain', '1', 'dark', 'teal', 'bag,', '2', 'vibrant', 'lime', 'bags.']\n",
      "['light', 'orange', 'bags', 'contain', '3', 'light', 'gold', 'bags,', '4', 'clear', 'plum', 'bags,', '4', 'dotted', 'indigo', 'bags.']\n",
      "['plaid', 'cyan', 'bags', 'contain', '1', 'pale', 'magenta', 'bag.']\n",
      "['wavy', 'chartreuse', 'bags', 'contain', '2', 'posh', 'green', 'bags,', '5', 'dotted', 'purple', 'bags,', '2', 'dark', 'tomato', 'bags,', '3', 'muted', 'gray', 'bags.']\n",
      "['light', 'coral', 'bags', 'contain', '5', 'clear', 'gray', 'bags,', '2', 'posh', 'purple', 'bags,', '2', 'mirrored', 'violet', 'bags.']\n",
      "['dull', 'violet', 'bags', 'contain', '3', 'dotted', 'blue', 'bags,', '5', 'mirrored', 'tomato', 'bags,', '1', 'dull', 'chartreuse', 'bag,', '2', 'posh', 'beige', 'bags.']\n",
      "['bright', 'tomato', 'bags', 'contain', '3', 'vibrant', 'red', 'bags,', '3', 'muted', 'gray', 'bags.']\n",
      "['mirrored', 'magenta', 'bags', 'contain', '4', 'wavy', 'brown', 'bags.']\n",
      "['muted', 'indigo', 'bags', 'contain', '4', 'wavy', 'chartreuse', 'bags,', '3', 'vibrant', 'indigo', 'bags,', '2', 'posh', 'magenta', 'bags,', '1', 'plaid', 'crimson', 'bag.']\n",
      "['bright', 'maroon', 'bags', 'contain', '2', 'dull', 'violet', 'bags,', '2', 'faded', 'tan', 'bags,', '3', 'striped', 'gray', 'bags,', '5', 'pale', 'magenta', 'bags.']\n",
      "['dark', 'tomato', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['pale', 'fuchsia', 'bags', 'contain', '3', 'drab', 'silver', 'bags,', '4', 'faded', 'purple', 'bags,', '2', 'mirrored', 'cyan', 'bags,', '5', 'dark', 'bronze', 'bags.']\n",
      "['dull', 'black', 'bags', 'contain', '1', 'dull', 'indigo', 'bag,', '1', 'wavy', 'brown', 'bag,', '5', 'striped', 'gray', 'bags.']\n",
      "['pale', 'white', 'bags', 'contain', '3', 'light', 'gray', 'bags,', '2', 'plaid', 'lavender', 'bags,', '1', 'wavy', 'maroon', 'bag.']\n",
      "['shiny', 'turquoise', 'bags', 'contain', '4', 'pale', 'red', 'bags.']\n",
      "['drab', 'brown', 'bags', 'contain', '5', 'mirrored', 'plum', 'bags,', '4', 'dotted', 'red', 'bags.']\n",
      "['bright', 'green', 'bags', 'contain', '1', 'dull', 'lime', 'bag,', '2', 'clear', 'lavender', 'bags.']\n",
      "['wavy', 'blue', 'bags', 'contain', '4', 'dotted', 'purple', 'bags.']\n",
      "['muted', 'aqua', 'bags', 'contain', '5', 'faded', 'plum', 'bags,', '3', 'plaid', 'plum', 'bags,', '4', 'dotted', 'tan', 'bags,', '1', 'clear', 'gray', 'bag.']\n",
      "['clear', 'yellow', 'bags', 'contain', '4', 'dotted', 'indigo', 'bags,', '3', 'vibrant', 'aqua', 'bags,', '4', 'vibrant', 'orange', 'bags.']\n",
      "['mirrored', 'gray', 'bags', 'contain', '4', 'shiny', 'crimson', 'bags,', '2', 'mirrored', 'coral', 'bags,', '1', 'dotted', 'tan', 'bag,', '4', 'posh', 'cyan', 'bags.']\n",
      "['dark', 'maroon', 'bags', 'contain', '1', 'dark', 'salmon', 'bag,', '3', 'muted', 'coral', 'bags.']\n",
      "['posh', 'plum', 'bags', 'contain', '1', 'mirrored', 'bronze', 'bag,', '4', 'plaid', 'purple', 'bags,', '3', 'vibrant', 'white', 'bags.']\n",
      "['bright', 'teal', 'bags', 'contain', '2', 'pale', 'aqua', 'bags,', '1', 'mirrored', 'black', 'bag.']\n",
      "['wavy', 'teal', 'bags', 'contain', '5', 'plaid', 'tan', 'bags,', '3', 'dull', 'black', 'bags,', '1', 'bright', 'teal', 'bag,', '3', 'clear', 'teal', 'bags.']\n",
      "['dotted', 'magenta', 'bags', 'contain', '1', 'plaid', 'plum', 'bag,', '5', 'plaid', 'salmon', 'bags,', '3', 'light', 'gold', 'bags.']\n",
      "['faded', 'tomato', 'bags', 'contain', '1', 'dark', 'bronze', 'bag,', '2', 'faded', 'purple', 'bags,', '4', 'vibrant', 'red', 'bags,', '4', 'pale', 'lavender', 'bags.']\n",
      "['dull', 'blue', 'bags', 'contain', '3', 'dotted', 'bronze', 'bags,', '2', 'shiny', 'olive', 'bags,', '3', 'muted', 'gold', 'bags.']\n",
      "['posh', 'aqua', 'bags', 'contain', '5', 'vibrant', 'orange', 'bags,', '1', 'vibrant', 'olive', 'bag.']\n",
      "['mirrored', 'black', 'bags', 'contain', '3', 'dark', 'teal', 'bags,', '4', 'plaid', 'chartreuse', 'bags,', '2', 'light', 'salmon', 'bags,', '2', 'vibrant', 'white', 'bags.']\n",
      "['wavy', 'violet', 'bags', 'contain', '5', 'vibrant', 'indigo', 'bags.']\n",
      "['vibrant', 'blue', 'bags', 'contain', '4', 'shiny', 'olive', 'bags,', '4', 'light', 'olive', 'bags,', '2', 'muted', 'green', 'bags.']\n",
      "['dotted', 'green', 'bags', 'contain', '3', 'shiny', 'violet', 'bags,', '3', 'posh', 'black', 'bags,', '3', 'dark', 'lime', 'bags.']\n",
      "['wavy', 'cyan', 'bags', 'contain', '2', 'muted', 'gray', 'bags,', '3', 'vibrant', 'olive', 'bags,', '4', 'striped', 'olive', 'bags,', '4', 'drab', 'silver', 'bags.']\n",
      "['faded', 'maroon', 'bags', 'contain', '5', 'bright', 'yellow', 'bags,', '2', 'bright', 'tomato', 'bags,', '5', 'mirrored', 'magenta', 'bags.']\n",
      "['dull', 'olive', 'bags', 'contain', '1', 'bright', 'plum', 'bag,', '2', 'pale', 'crimson', 'bags.']\n",
      "['clear', 'lime', 'bags', 'contain', '5', 'striped', 'blue', 'bags,', '5', 'wavy', 'blue', 'bags,', '3', 'drab', 'tan', 'bags,', '1', 'shiny', 'olive', 'bag.']\n",
      "['striped', 'yellow', 'bags', 'contain', '1', 'mirrored', 'red', 'bag.']\n",
      "['plaid', 'magenta', 'bags', 'contain', '2', 'clear', 'yellow', 'bags,', '1', 'pale', 'coral', 'bag,', '3', 'muted', 'bronze', 'bags.']\n",
      "['light', 'lime', 'bags', 'contain', '1', 'dim', 'turquoise', 'bag.']\n",
      "['striped', 'brown', 'bags', 'contain', '3', 'mirrored', 'brown', 'bags,', '4', 'clear', 'cyan', 'bags,', '5', 'bright', 'white', 'bags,', '1', 'muted', 'maroon', 'bag.']\n",
      "['dotted', 'indigo', 'bags', 'contain', '3', 'light', 'olive', 'bags,', '1', 'dull', 'chartreuse', 'bag.']\n",
      "['shiny', 'tan', 'bags', 'contain', '2', 'dull', 'lime', 'bags,', '5', 'shiny', 'black', 'bags,', '5', 'dull', 'teal', 'bags.']\n",
      "['clear', 'olive', 'bags', 'contain', '5', 'drab', 'coral', 'bags,', '4', 'striped', 'aqua', 'bags,', '4', 'dotted', 'lavender', 'bags.']\n",
      "['plaid', 'chartreuse', 'bags', 'contain', '1', 'plaid', 'red', 'bag,', '4', 'faded', 'tomato', 'bags.']\n",
      "['dotted', 'olive', 'bags', 'contain', '2', 'dull', 'yellow', 'bags.']\n",
      "['faded', 'lime', 'bags', 'contain', '5', 'dotted', 'aqua', 'bags,', '4', 'shiny', 'silver', 'bags,', '4', 'muted', 'white', 'bags.']\n",
      "['vibrant', 'silver', 'bags', 'contain', '4', 'dotted', 'teal', 'bags,', '3', 'posh', 'olive', 'bags.']\n",
      "['striped', 'beige', 'bags', 'contain', '2', 'vibrant', 'white', 'bags,', '3', 'dark', 'gold', 'bags,', '4', 'posh', 'violet', 'bags,', '4', 'bright', 'chartreuse', 'bags.']\n",
      "['dim', 'plum', 'bags', 'contain', '2', 'striped', 'indigo', 'bags,', '2', 'vibrant', 'gold', 'bags.']\n",
      "['clear', 'crimson', 'bags', 'contain', '5', 'vibrant', 'red', 'bags.']\n",
      "['plaid', 'maroon', 'bags', 'contain', '4', 'clear', 'crimson', 'bags.']\n",
      "['drab', 'coral', 'bags', 'contain', '2', 'plaid', 'plum', 'bags.']\n",
      "['dull', 'bronze', 'bags', 'contain', '4', 'pale', 'black', 'bags,', '1', 'dull', 'tan', 'bag,', '5', 'dull', 'cyan', 'bags,', '4', 'pale', 'lavender', 'bags.']\n",
      "['wavy', 'bronze', 'bags', 'contain', '4', 'posh', 'coral', 'bags,', '2', 'bright', 'silver', 'bags.']\n",
      "['dull', 'aqua', 'bags', 'contain', '3', 'dotted', 'orange', 'bags,', '3', 'pale', 'teal', 'bags.']\n",
      "['muted', 'plum', 'bags', 'contain', '1', 'light', 'blue', 'bag,', '2', 'muted', 'maroon', 'bags,', '4', 'dull', 'olive', 'bags.']\n",
      "['vibrant', 'tan', 'bags', 'contain', '4', 'drab', 'teal', 'bags.']\n",
      "['dull', 'tomato', 'bags', 'contain', '5', 'dull', 'white', 'bags.']\n",
      "['muted', 'yellow', 'bags', 'contain', '3', 'dark', 'yellow', 'bags,', '5', 'faded', 'beige', 'bags.']\n",
      "['shiny', 'white', 'bags', 'contain', '4', 'bright', 'silver', 'bags.']\n",
      "['muted', 'crimson', 'bags', 'contain', '1', 'clear', 'maroon', 'bag.']\n",
      "['muted', 'violet', 'bags', 'contain', '3', 'dotted', 'yellow', 'bags,', '1', 'light', 'indigo', 'bag,', '4', 'mirrored', 'black', 'bags,', '5', 'drab', 'lime', 'bags.']\n",
      "['posh', 'white', 'bags', 'contain', '3', 'faded', 'brown', 'bags,', '2', 'dull', 'yellow', 'bags.']\n",
      "['wavy', 'crimson', 'bags', 'contain', '3', 'shiny', 'black', 'bags,', '2', 'dotted', 'blue', 'bags,', '4', 'dark', 'maroon', 'bags.']\n",
      "['clear', 'salmon', 'bags', 'contain', '1', 'mirrored', 'magenta', 'bag,', '4', 'bright', 'chartreuse', 'bags,', '5', 'vibrant', 'black', 'bags,', '2', 'vibrant', 'chartreuse', 'bags.']\n",
      "['pale', 'teal', 'bags', 'contain', '5', 'mirrored', 'white', 'bags,', '2', 'plaid', 'orange', 'bags,', '4', 'muted', 'lime', 'bags.']\n",
      "['light', 'aqua', 'bags', 'contain', '2', 'shiny', 'salmon', 'bags,', '3', 'dark', 'tomato', 'bags,', '1', 'mirrored', 'purple', 'bag.']\n",
      "['clear', 'beige', 'bags', 'contain', '1', 'muted', 'crimson', 'bag.']\n",
      "['vibrant', 'olive', 'bags', 'contain', '5', 'dark', 'tomato', 'bags,', '1', 'pale', 'gold', 'bag,', '4', 'muted', 'tan', 'bags.']\n",
      "['plaid', 'brown', 'bags', 'contain', '3', 'mirrored', 'lavender', 'bags,', '1', 'muted', 'crimson', 'bag,', '3', 'muted', 'green', 'bags,', '1', 'bright', 'lavender', 'bag.']\n",
      "['dim', 'magenta', 'bags', 'contain', '4', 'pale', 'fuchsia', 'bags,', '3', 'drab', 'black', 'bags,', '4', 'plaid', 'orange', 'bags.']\n",
      "['bright', 'purple', 'bags', 'contain', '3', 'muted', 'gray', 'bags,', '3', 'pale', 'coral', 'bags.']\n",
      "['posh', 'indigo', 'bags', 'contain', '2', 'bright', 'beige', 'bags,', '2', 'dim', 'tomato', 'bags.']\n",
      "['drab', 'lavender', 'bags', 'contain', '2', 'dotted', 'chartreuse', 'bags,', '1', 'posh', 'green', 'bag,', '3', 'light', 'silver', 'bags,', '1', 'dotted', 'black', 'bag.']\n",
      "['pale', 'crimson', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['posh', 'gray', 'bags', 'contain', '1', 'muted', 'green', 'bag.']\n",
      "['shiny', 'lime', 'bags', 'contain', '3', 'mirrored', 'maroon', 'bags,', '1', 'posh', 'crimson', 'bag,', '4', 'mirrored', 'orange', 'bags,', '2', 'posh', 'olive', 'bags.']\n",
      "['muted', 'beige', 'bags', 'contain', '1', 'posh', 'tan', 'bag,', '3', 'posh', 'olive', 'bags,', '1', 'faded', 'white', 'bag,', '2', 'posh', 'green', 'bags.']\n",
      "['light', 'black', 'bags', 'contain', '3', 'striped', 'green', 'bags,', '2', 'pale', 'salmon', 'bags,', '3', 'muted', 'crimson', 'bags.']\n",
      "['dark', 'gold', 'bags', 'contain', '5', 'striped', 'maroon', 'bags,', '2', 'pale', 'fuchsia', 'bags,', '3', 'light', 'gold', 'bags.']\n",
      "['light', 'bronze', 'bags', 'contain', '2', 'clear', 'purple', 'bags,', '4', 'dim', 'crimson', 'bags.']\n",
      "['muted', 'blue', 'bags', 'contain', '1', 'faded', 'gray', 'bag,', '4', 'muted', 'salmon', 'bags,', '5', 'dull', 'bronze', 'bags.']\n",
      "['vibrant', 'orange', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['dim', 'lavender', 'bags', 'contain', '1', 'vibrant', 'indigo', 'bag.']\n",
      "['posh', 'fuchsia', 'bags', 'contain', '3', 'clear', 'fuchsia', 'bags,', '2', 'shiny', 'green', 'bags,', '3', 'plaid', 'plum', 'bags.']\n",
      "['dim', 'tan', 'bags', 'contain', '5', 'pale', 'plum', 'bags,', '3', 'posh', 'gray', 'bags,', '1', 'clear', 'yellow', 'bag.']\n",
      "['pale', 'lime', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['striped', 'blue', 'bags', 'contain', '5', 'pale', 'black', 'bags.']\n",
      "['shiny', 'tomato', 'bags', 'contain', '1', 'dim', 'fuchsia', 'bag,', '5', 'faded', 'blue', 'bags,', '3', 'muted', 'brown', 'bags,', '3', 'mirrored', 'salmon', 'bags.']\n",
      "['dotted', 'orange', 'bags', 'contain', '4', 'bright', 'tomato', 'bags,', '1', 'light', 'silver', 'bag.']\n",
      "['muted', 'tan', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['pale', 'black', 'bags', 'contain', '2', 'dull', 'brown', 'bags,', '4', 'mirrored', 'chartreuse', 'bags,', '2', 'dim', 'aqua', 'bags.']\n",
      "['shiny', 'purple', 'bags', 'contain', '3', 'dotted', 'indigo', 'bags,', '5', 'vibrant', 'gold', 'bags,', '2', 'light', 'chartreuse', 'bags,', '4', 'clear', 'magenta', 'bags.']\n",
      "['dull', 'brown', 'bags', 'contain', '2', 'bright', 'beige', 'bags,', '4', 'vibrant', 'orange', 'bags,', '2', 'bright', 'tomato', 'bags,', '4', 'clear', 'lavender', 'bags.']\n",
      "['plaid', 'aqua', 'bags', 'contain', '3', 'plaid', 'indigo', 'bags.']\n",
      "['dark', 'olive', 'bags', 'contain', '1', 'pale', 'plum', 'bag,', '4', 'dim', 'maroon', 'bags.']\n",
      "['dark', 'silver', 'bags', 'contain', '3', 'shiny', 'blue', 'bags,', '2', 'muted', 'gray', 'bags,', '4', 'drab', 'coral', 'bags.']\n",
      "['clear', 'turquoise', 'bags', 'contain', '5', 'light', 'violet', 'bags,', '3', 'drab', 'yellow', 'bags.']\n",
      "['wavy', 'brown', 'bags', 'contain', '3', 'shiny', 'coral', 'bags,', '3', 'shiny', 'salmon', 'bags,', '1', 'drab', 'magenta', 'bag.']\n",
      "['dim', 'indigo', 'bags', 'contain', '5', 'bright', 'green', 'bags.']\n",
      "['mirrored', 'gold', 'bags', 'contain', '1', 'plaid', 'magenta', 'bag,', '2', 'plaid', 'gold', 'bags,', '4', 'light', 'turquoise', 'bags.']\n",
      "['drab', 'red', 'bags', 'contain', '3', 'mirrored', 'bronze', 'bags.']\n",
      "['faded', 'bronze', 'bags', 'contain', '1', 'vibrant', 'aqua', 'bag,', '2', 'clear', 'tomato', 'bags,', '2', 'dull', 'tan', 'bags.']\n",
      "['bright', 'lavender', 'bags', 'contain', '4', 'drab', 'coral', 'bags,', '1', 'bright', 'green', 'bag.']\n",
      "['wavy', 'lavender', 'bags', 'contain', '2', 'wavy', 'green', 'bags,', '4', 'drab', 'silver', 'bags,', '5', 'light', 'turquoise', 'bags.']\n",
      "['wavy', 'salmon', 'bags', 'contain', '2', 'dotted', 'gray', 'bags,', '4', 'bright', 'chartreuse', 'bags,', '4', 'striped', 'gray', 'bags.']\n",
      "['dotted', 'yellow', 'bags', 'contain', '4', 'dark', 'salmon', 'bags,', '1', 'posh', 'tan', 'bag,', '4', 'drab', 'tomato', 'bags,', '4', 'vibrant', 'chartreuse', 'bags.']\n",
      "['dull', 'turquoise', 'bags', 'contain', '5', 'drab', 'silver', 'bags,', '1', 'dark', 'orange', 'bag.']\n",
      "['pale', 'gray', 'bags', 'contain', '4', 'dull', 'aqua', 'bags,', '4', 'faded', 'gold', 'bags,', '2', 'mirrored', 'orange', 'bags,', '2', 'dim', 'magenta', 'bags.']\n",
      "['dark', 'red', 'bags', 'contain', '2', 'bright', 'gray', 'bags,', '4', 'bright', 'black', 'bags.']\n",
      "['dim', 'fuchsia', 'bags', 'contain', '3', 'bright', 'magenta', 'bags,', '5', 'pale', 'crimson', 'bags.']\n",
      "['vibrant', 'lime', 'bags', 'contain', '2', 'wavy', 'maroon', 'bags,', '2', 'pale', 'magenta', 'bags,', '4', 'pale', 'crimson', 'bags,', '3', 'drab', 'orange', 'bags.']\n",
      "['bright', 'bronze', 'bags', 'contain', '4', 'vibrant', 'black', 'bags,', '3', 'drab', 'fuchsia', 'bags,', '3', 'striped', 'cyan', 'bags,', '3', 'dotted', 'blue', 'bags.']\n",
      "['muted', 'coral', 'bags', 'contain', '3', 'wavy', 'white', 'bags,', '1', 'plaid', 'tan', 'bag.']\n",
      "['wavy', 'white', 'bags', 'contain', '2', 'drab', 'maroon', 'bags.']\n",
      "['pale', 'coral', 'bags', 'contain', '3', 'dotted', 'bronze', 'bags,', '1', 'dull', 'gold', 'bag.']\n",
      "['drab', 'white', 'bags', 'contain', '3', 'drab', 'silver', 'bags,', '3', 'bright', 'tomato', 'bags,', '1', 'bright', 'silver', 'bag.']\n",
      "['light', 'olive', 'bags', 'contain', '3', 'muted', 'tan', 'bags,', '2', 'mirrored', 'tomato', 'bags.']\n",
      "['mirrored', 'tomato', 'bags', 'contain', '2', 'dark', 'tomato', 'bags,', '3', 'shiny', 'gold', 'bags.']\n",
      "['light', 'crimson', 'bags', 'contain', '4', 'clear', 'magenta', 'bags,', '2', 'plaid', 'coral', 'bags,', '5', 'dull', 'chartreuse', 'bags,', '5', 'dark', 'teal', 'bags.']\n",
      "['bright', 'cyan', 'bags', 'contain', '1', 'clear', 'chartreuse', 'bag,', '1', 'striped', 'brown', 'bag,', '5', 'light', 'tomato', 'bags,', '4', 'dark', 'coral', 'bags.']\n",
      "['vibrant', 'fuchsia', 'bags', 'contain', '3', 'dull', 'white', 'bags,', '1', 'dim', 'purple', 'bag,', '5', 'shiny', 'yellow', 'bags.']\n",
      "['drab', 'gold', 'bags', 'contain', '5', 'wavy', 'chartreuse', 'bags.']\n",
      "['plaid', 'yellow', 'bags', 'contain', '4', 'faded', 'plum', 'bags,', '1', 'faded', 'indigo', 'bag,', '2', 'drab', 'purple', 'bags,', '1', 'light', 'purple', 'bag.']\n",
      "['bright', 'black', 'bags', 'contain', '2', 'clear', 'yellow', 'bags,', '1', 'dotted', 'red', 'bag,', '4', 'dim', 'white', 'bags.']\n",
      "['pale', 'maroon', 'bags', 'contain', '2', 'vibrant', 'tomato', 'bags,', '3', 'mirrored', 'tomato', 'bags.']\n",
      "['wavy', 'gray', 'bags', 'contain', '2', 'wavy', 'cyan', 'bags,', '2', 'dark', 'tomato', 'bags,', '4', 'vibrant', 'orange', 'bags,', '5', 'pale', 'silver', 'bags.']\n",
      "['faded', 'salmon', 'bags', 'contain', '4', 'bright', 'plum', 'bags.']\n",
      "['shiny', 'teal', 'bags', 'contain', '4', 'dark', 'magenta', 'bags.']\n",
      "['dim', 'bronze', 'bags', 'contain', '5', 'striped', 'olive', 'bags,', '5', 'dotted', 'plum', 'bags,', '4', 'dark', 'purple', 'bags.']\n",
      "['dotted', 'lavender', 'bags', 'contain', '4', 'striped', 'indigo', 'bags,', '2', 'mirrored', 'red', 'bags,', '2', 'bright', 'chartreuse', 'bags,', '4', 'bright', 'teal', 'bags.']\n",
      "['plaid', 'beige', 'bags', 'contain', '4', 'vibrant', 'green', 'bags,', '3', 'striped', 'violet', 'bags,', '5', 'vibrant', 'blue', 'bags.']\n",
      "['dull', 'purple', 'bags', 'contain', '1', 'dark', 'beige', 'bag,', '1', 'drab', 'silver', 'bag,', '4', 'faded', 'fuchsia', 'bags,', '2', 'vibrant', 'olive', 'bags.']\n",
      "['bright', 'olive', 'bags', 'contain', '3', 'faded', 'salmon', 'bags,', '1', 'wavy', 'magenta', 'bag,', '5', 'dim', 'yellow', 'bags.']\n",
      "['mirrored', 'maroon', 'bags', 'contain', '3', 'bright', 'magenta', 'bags,', '5', 'pale', 'lime', 'bags,', '3', 'striped', 'olive', 'bags.']\n",
      "['clear', 'brown', 'bags', 'contain', '2', 'mirrored', 'orange', 'bags,', '5', 'bright', 'cyan', 'bags.']\n",
      "['drab', 'teal', 'bags', 'contain', '3', 'dull', 'olive', 'bags.']\n",
      "['clear', 'red', 'bags', 'contain', '1', 'bright', 'maroon', 'bag.']\n",
      "['vibrant', 'black', 'bags', 'contain', '4', 'pale', 'fuchsia', 'bags,', '3', 'clear', 'lavender', 'bags,', '2', 'shiny', 'blue', 'bags,', '3', 'dotted', 'blue', 'bags.']\n",
      "['faded', 'white', 'bags', 'contain', '3', 'wavy', 'coral', 'bags,', '4', 'faded', 'yellow', 'bags,', '5', 'shiny', 'olive', 'bags,', '1', 'plaid', 'orange', 'bag.']\n",
      "['dotted', 'aqua', 'bags', 'contain', '1', 'wavy', 'white', 'bag,', '3', 'dotted', 'blue', 'bags,', '5', 'pale', 'lavender', 'bags,', '4', 'clear', 'aqua', 'bags.']\n",
      "['pale', 'blue', 'bags', 'contain', '3', 'dim', 'salmon', 'bags,', '3', 'muted', 'cyan', 'bags,', '5', 'pale', 'fuchsia', 'bags.']\n",
      "['dim', 'turquoise', 'bags', 'contain', '4', 'vibrant', 'chartreuse', 'bags,', '2', 'dark', 'silver', 'bags,', '3', 'pale', 'gold', 'bags.']\n",
      "['dull', 'magenta', 'bags', 'contain', '3', 'muted', 'salmon', 'bags,', '4', 'dotted', 'gray', 'bags,', '3', 'light', 'salmon', 'bags.']\n",
      "['dotted', 'coral', 'bags', 'contain', '2', 'mirrored', 'tomato', 'bags,', '1', 'vibrant', 'teal', 'bag,', '3', 'dull', 'crimson', 'bags.']\n",
      "['dull', 'beige', 'bags', 'contain', '2', 'faded', 'fuchsia', 'bags.']\n",
      "['shiny', 'gold', 'bags', 'contain', '4', 'bright', 'beige', 'bags,', '3', 'dull', 'crimson', 'bags,', '4', 'mirrored', 'maroon', 'bags,', '3', 'bright', 'tomato', 'bags.']\n",
      "['pale', 'indigo', 'bags', 'contain', '2', 'dotted', 'teal', 'bags,', '3', 'faded', 'teal', 'bags,', '4', 'wavy', 'indigo', 'bags.']\n",
      "['shiny', 'magenta', 'bags', 'contain', '5', 'bright', 'tomato', 'bags,', '5', 'dull', 'lime', 'bags,', '5', 'mirrored', 'bronze', 'bags,', '2', 'dim', 'black', 'bags.']\n",
      "['muted', 'cyan', 'bags', 'contain', '2', 'dark', 'bronze', 'bags,', '5', 'drab', 'silver', 'bags,', '4', 'dotted', 'chartreuse', 'bags.']\n",
      "['plaid', 'orange', 'bags', 'contain', '4', 'light', 'plum', 'bags,', '5', 'shiny', 'salmon', 'bags,', '5', 'posh', 'beige', 'bags.']\n",
      "['shiny', 'green', 'bags', 'contain', '5', 'dotted', 'tan', 'bags,', '5', 'mirrored', 'olive', 'bags,', '1', 'dark', 'teal', 'bag.']\n",
      "['dull', 'maroon', 'bags', 'contain', '1', 'striped', 'black', 'bag,', '4', 'clear', 'green', 'bags.']\n",
      "['drab', 'aqua', 'bags', 'contain', '1', 'striped', 'indigo', 'bag,', '3', 'vibrant', 'white', 'bags.']\n",
      "['bright', 'gold', 'bags', 'contain', '4', 'mirrored', 'beige', 'bags,', '4', 'mirrored', 'yellow', 'bags.']\n",
      "['plaid', 'tan', 'bags', 'contain', '5', 'shiny', 'aqua', 'bags.']\n",
      "['striped', 'plum', 'bags', 'contain', '4', 'clear', 'magenta', 'bags,', '2', 'dark', 'gold', 'bags.']\n",
      "['vibrant', 'teal', 'bags', 'contain', '1', 'dim', 'aqua', 'bag,', '4', 'vibrant', 'violet', 'bags,', '3', 'plaid', 'olive', 'bags,', '1', 'mirrored', 'olive', 'bag.']\n",
      "['posh', 'bronze', 'bags', 'contain', '5', 'dark', 'tomato', 'bags,', '5', 'shiny', 'silver', 'bags.']\n",
      "['dim', 'orange', 'bags', 'contain', '4', 'dull', 'salmon', 'bags.']\n",
      "['striped', 'indigo', 'bags', 'contain', '4', 'drab', 'magenta', 'bags.']\n",
      "['vibrant', 'yellow', 'bags', 'contain', '4', 'drab', 'olive', 'bags,', '4', 'wavy', 'olive', 'bags,', '2', 'dark', 'teal', 'bags,', '2', 'faded', 'purple', 'bags.']\n",
      "['striped', 'purple', 'bags', 'contain', '5', 'pale', 'red', 'bags.']\n",
      "['dim', 'coral', 'bags', 'contain', '1', 'plaid', 'maroon', 'bag,', '2', 'pale', 'magenta', 'bags,', '1', 'pale', 'indigo', 'bag,', '2', 'dotted', 'turquoise', 'bags.']\n",
      "['muted', 'silver', 'bags', 'contain', '4', 'mirrored', 'turquoise', 'bags.']\n",
      "['posh', 'cyan', 'bags', 'contain', '3', 'dotted', 'purple', 'bags.']\n",
      "['plaid', 'lavender', 'bags', 'contain', '3', 'muted', 'gray', 'bags,', '1', 'light', 'plum', 'bag.']\n",
      "['faded', 'tan', 'bags', 'contain', '1', 'mirrored', 'cyan', 'bag,', '2', 'plaid', 'crimson', 'bags,', '5', 'mirrored', 'maroon', 'bags.']\n",
      "['clear', 'lavender', 'bags', 'contain', '4', 'pale', 'gold', 'bags,', '1', 'posh', 'lime', 'bag,', '4', 'pale', 'crimson', 'bags.']\n",
      "['dull', 'gray', 'bags', 'contain', '5', 'shiny', 'crimson', 'bags,', '5', 'wavy', 'cyan', 'bags,', '3', 'posh', 'lavender', 'bags.']\n",
      "['dull', 'green', 'bags', 'contain', '1', 'faded', 'bronze', 'bag,', '3', 'vibrant', 'indigo', 'bags,', '2', 'muted', 'fuchsia', 'bags,', '4', 'dotted', 'silver', 'bags.']\n",
      "['dark', 'magenta', 'bags', 'contain', '3', 'wavy', 'white', 'bags,', '3', 'plaid', 'plum', 'bags,', '4', 'wavy', 'lavender', 'bags,', '3', 'drab', 'magenta', 'bags.']\n",
      "['plaid', 'red', 'bags', 'contain', '1', 'bright', 'turquoise', 'bag.']\n",
      "['dull', 'coral', 'bags', 'contain', '4', 'clear', 'tomato', 'bags.']\n",
      "['posh', 'turquoise', 'bags', 'contain', '5', 'dull', 'gold', 'bags,', '4', 'mirrored', 'chartreuse', 'bags.']\n",
      "['drab', 'crimson', 'bags', 'contain', '2', 'dull', 'tomato', 'bags,', '5', 'posh', 'orange', 'bags,', '5', 'shiny', 'violet', 'bags.']\n",
      "['clear', 'tan', 'bags', 'contain', '1', 'pale', 'fuchsia', 'bag,', '4', 'light', 'aqua', 'bags,', '3', 'shiny', 'blue', 'bags,', '3', 'bright', 'turquoise', 'bags.']\n",
      "['dotted', 'brown', 'bags', 'contain', '4', 'drab', 'magenta', 'bags,', '5', 'plaid', 'crimson', 'bags,', '2', 'posh', 'beige', 'bags.']\n",
      "['light', 'silver', 'bags', 'contain', '3', 'mirrored', 'green', 'bags,', '5', 'mirrored', 'maroon', 'bags,', '5', 'shiny', 'blue', 'bags.']\n",
      "['dotted', 'gold', 'bags', 'contain', '2', 'dim', 'magenta', 'bags.']\n",
      "['drab', 'yellow', 'bags', 'contain', '5', 'pale', 'purple', 'bags.']\n",
      "['faded', 'lavender', 'bags', 'contain', '5', 'muted', 'cyan', 'bags.']\n",
      "['vibrant', 'beige', 'bags', 'contain', '4', 'clear', 'turquoise', 'bags,', '2', 'dark', 'fuchsia', 'bags,', '1', 'pale', 'gray', 'bag,', '5', 'dim', 'beige', 'bags.']\n",
      "['clear', 'fuchsia', 'bags', 'contain', '1', 'pale', 'fuchsia', 'bag,', '1', 'wavy', 'turquoise', 'bag,', '5', 'faded', 'gray', 'bags.']\n",
      "['shiny', 'chartreuse', 'bags', 'contain', '4', 'vibrant', 'green', 'bags,', '1', 'dotted', 'teal', 'bag.']\n",
      "['dim', 'purple', 'bags', 'contain', '1', 'bright', 'turquoise', 'bag.']\n",
      "['clear', 'indigo', 'bags', 'contain', '4', 'light', 'white', 'bags,', '3', 'vibrant', 'orange', 'bags.']\n",
      "['wavy', 'turquoise', 'bags', 'contain', '5', 'bright', 'magenta', 'bags.']\n",
      "['vibrant', 'chartreuse', 'bags', 'contain', '4', 'mirrored', 'chartreuse', 'bags,', '2', 'muted', 'tan', 'bags,', '2', 'plaid', 'lime', 'bags,', '3', 'striped', 'olive', 'bags.']\n",
      "['dark', 'chartreuse', 'bags', 'contain', '5', 'shiny', 'blue', 'bags.']\n",
      "['clear', 'plum', 'bags', 'contain', '3', 'pale', 'lime', 'bags.']\n",
      "['dotted', 'tomato', 'bags', 'contain', '5', 'bright', 'red', 'bags,', '2', 'bright', 'olive', 'bags,', '5', 'drab', 'silver', 'bags,', '4', 'clear', 'magenta', 'bags.']\n",
      "['mirrored', 'beige', 'bags', 'contain', '4', 'light', 'violet', 'bags,', '5', 'mirrored', 'salmon', 'bags,', '4', 'dim', 'yellow', 'bags,', '5', 'bright', 'yellow', 'bags.']\n",
      "['posh', 'teal', 'bags', 'contain', '2', 'plaid', 'turquoise', 'bags,', '3', 'pale', 'salmon', 'bags,', '1', 'striped', 'plum', 'bag.']\n",
      "['dull', 'chartreuse', 'bags', 'contain', '5', 'pale', 'lavender', 'bags,', '1', 'bright', 'turquoise', 'bag,', '3', 'pale', 'beige', 'bags.']\n",
      "['mirrored', 'lavender', 'bags', 'contain', '4', 'vibrant', 'tomato', 'bags,', '2', 'plaid', 'tan', 'bags,', '5', 'bright', 'magenta', 'bags.']\n",
      "['dark', 'gray', 'bags', 'contain', '5', 'wavy', 'turquoise', 'bags,', '4', 'wavy', 'gray', 'bags,', '4', 'dark', 'bronze', 'bags,', '4', 'pale', 'aqua', 'bags.']\n",
      "['dark', 'white', 'bags', 'contain', '4', 'clear', 'maroon', 'bags,', '2', 'vibrant', 'olive', 'bags,', '1', 'dull', 'lime', 'bag,', '1', 'faded', 'lime', 'bag.']\n",
      "['dull', 'indigo', 'bags', 'contain', '4', 'clear', 'fuchsia', 'bags,', '3', 'dotted', 'tan', 'bags,', '1', 'plaid', 'cyan', 'bag.']\n",
      "['striped', 'tan', 'bags', 'contain', '3', 'pale', 'brown', 'bags.']\n",
      "['dull', 'gold', 'bags', 'contain', '2', 'dark', 'yellow', 'bags,', '3', 'dull', 'olive', 'bags.']\n",
      "['light', 'lavender', 'bags', 'contain', '2', 'plaid', 'red', 'bags,', '5', 'dotted', 'purple', 'bags,', '1', 'bright', 'beige', 'bag,', '3', 'pale', 'beige', 'bags.']\n",
      "['faded', 'teal', 'bags', 'contain', '4', 'mirrored', 'olive', 'bags.']\n",
      "['plaid', 'salmon', 'bags', 'contain', '1', 'dark', 'bronze', 'bag,', '5', 'pale', 'yellow', 'bags,', '1', 'striped', 'cyan', 'bag,', '2', 'muted', 'cyan', 'bags.']\n",
      "['dotted', 'purple', 'bags', 'contain', '1', 'bright', 'turquoise', 'bag,', '1', 'posh', 'green', 'bag.']\n",
      "['dull', 'silver', 'bags', 'contain', '3', 'striped', 'salmon', 'bags,', '4', 'posh', 'violet', 'bags,', '4', 'striped', 'orange', 'bags.']\n",
      "['drab', 'chartreuse', 'bags', 'contain', '4', 'pale', 'lavender', 'bags.']\n",
      "['striped', 'coral', 'bags', 'contain', '5', 'bright', 'gray', 'bags,', '4', 'dark', 'teal', 'bags,', '5', 'dotted', 'purple', 'bags.']\n",
      "['wavy', 'olive', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['plaid', 'olive', 'bags', 'contain', '1', 'pale', 'black', 'bag,', '3', 'clear', 'plum', 'bags.']\n",
      "['drab', 'black', 'bags', 'contain', '3', 'striped', 'olive', 'bags,', '2', 'mirrored', 'chartreuse', 'bags,', '5', 'pale', 'silver', 'bags.']\n",
      "['striped', 'lime', 'bags', 'contain', '3', 'dark', 'chartreuse', 'bags,', '5', 'pale', 'silver', 'bags,', '2', 'plaid', 'crimson', 'bags,', '4', 'clear', 'fuchsia', 'bags.']\n",
      "['drab', 'beige', 'bags', 'contain', '4', 'dim', 'black', 'bags,', '4', 'striped', 'black', 'bags,', '4', 'dull', 'crimson', 'bags,', '5', 'dark', 'gray', 'bags.']\n",
      "['muted', 'tomato', 'bags', 'contain', '3', 'light', 'bronze', 'bags,', '3', 'pale', 'salmon', 'bags,', '2', 'vibrant', 'chartreuse', 'bags.']\n",
      "['bright', 'fuchsia', 'bags', 'contain', '5', 'drab', 'orange', 'bags,', '3', 'pale', 'black', 'bags,', '3', 'mirrored', 'white', 'bags,', '5', 'faded', 'tomato', 'bags.']\n",
      "['vibrant', 'gray', 'bags', 'contain', '4', 'posh', 'lime', 'bags,', '2', 'dark', 'purple', 'bags,', '4', 'clear', 'aqua', 'bags.']\n",
      "['shiny', 'yellow', 'bags', 'contain', '5', 'bright', 'beige', 'bags,', '2', 'vibrant', 'red', 'bags,', '5', 'dim', 'yellow', 'bags,', '2', 'vibrant', 'yellow', 'bags.']\n",
      "['posh', 'coral', 'bags', 'contain', '5', 'drab', 'indigo', 'bags.']\n",
      "['muted', 'fuchsia', 'bags', 'contain', '5', 'shiny', 'silver', 'bags,', '2', 'dotted', 'salmon', 'bags,', '1', 'muted', 'tan', 'bag.']\n",
      "['muted', 'brown', 'bags', 'contain', '4', 'clear', 'maroon', 'bags,', '5', 'dim', 'purple', 'bags,', '4', 'wavy', 'maroon', 'bags,', '2', 'muted', 'red', 'bags.']\n",
      "['posh', 'chartreuse', 'bags', 'contain', '5', 'muted', 'tan', 'bags,', '3', 'drab', 'teal', 'bags.']\n",
      "['vibrant', 'brown', 'bags', 'contain', '1', 'wavy', 'bronze', 'bag,', '5', 'bright', 'red', 'bags,', '4', 'muted', 'fuchsia', 'bags,', '4', 'clear', 'fuchsia', 'bags.']\n",
      "['posh', 'purple', 'bags', 'contain', '2', 'drab', 'turquoise', 'bags,', '5', 'striped', 'blue', 'bags,', '1', 'muted', 'cyan', 'bag.']\n",
      "['plaid', 'lime', 'bags', 'contain', '3', 'muted', 'gray', 'bags,', '5', 'vibrant', 'red', 'bags,', '1', 'wavy', 'gray', 'bag,', '1', 'pale', 'silver', 'bag.']\n",
      "['posh', 'violet', 'bags', 'contain', '2', 'faded', 'crimson', 'bags,', '1', 'shiny', 'olive', 'bag,', '3', 'bright', 'magenta', 'bags,', '1', 'drab', 'silver', 'bag.']\n",
      "['striped', 'gold', 'bags', 'contain', '5', 'faded', 'salmon', 'bags,', '2', 'drab', 'bronze', 'bags,', '2', 'dark', 'plum', 'bags.']\n",
      "['striped', 'gray', 'bags', 'contain', '2', 'mirrored', 'crimson', 'bags,', '5', 'faded', 'beige', 'bags,', '1', 'dull', 'red', 'bag.']\n",
      "['dim', 'blue', 'bags', 'contain', '2', 'dark', 'coral', 'bags,', '3', 'dim', 'yellow', 'bags,', '1', 'dull', 'salmon', 'bag.']\n",
      "['bright', 'silver', 'bags', 'contain', '2', 'mirrored', 'tomato', 'bags,', '3', 'bright', 'plum', 'bags,', '4', 'pale', 'lavender', 'bags,', '1', 'clear', 'tomato', 'bag.']\n",
      "['striped', 'red', 'bags', 'contain', '4', 'light', 'yellow', 'bags,', '5', 'mirrored', 'white', 'bags,', '5', 'plaid', 'gold', 'bags.']\n",
      "['shiny', 'maroon', 'bags', 'contain', '3', 'wavy', 'cyan', 'bags,', '1', 'mirrored', 'tomato', 'bag,', '1', 'mirrored', 'coral', 'bag.']\n",
      "['mirrored', 'brown', 'bags', 'contain', '2', 'mirrored', 'olive', 'bags,', '3', 'mirrored', 'green', 'bags,', '1', 'dim', 'tomato', 'bag.']\n",
      "['striped', 'olive', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['striped', 'violet', 'bags', 'contain', '5', 'bright', 'tomato', 'bags.']\n",
      "['mirrored', 'aqua', 'bags', 'contain', '4', 'dark', 'gray', 'bags,', '5', 'shiny', 'blue', 'bags,', '2', 'pale', 'silver', 'bags.']\n",
      "['plaid', 'white', 'bags', 'contain', '3', 'dim', 'maroon', 'bags,', '2', 'dim', 'tan', 'bags.']\n",
      "['drab', 'orange', 'bags', 'contain', '5', 'striped', 'olive', 'bags.']\n",
      "['dark', 'brown', 'bags', 'contain', '2', 'mirrored', 'bronze', 'bags,', '5', 'clear', 'maroon', 'bags,', '2', 'dull', 'lime', 'bags.']\n",
      "['dotted', 'silver', 'bags', 'contain', '1', 'dark', 'gold', 'bag,', '1', 'drab', 'black', 'bag,', '3', 'pale', 'aqua', 'bags.']\n",
      "['pale', 'plum', 'bags', 'contain', '5', 'striped', 'maroon', 'bags,', '5', 'dotted', 'purple', 'bags,', '4', 'shiny', 'magenta', 'bags.']\n",
      "['faded', 'indigo', 'bags', 'contain', '1', 'posh', 'cyan', 'bag,', '5', 'bright', 'green', 'bags.']\n",
      "['mirrored', 'teal', 'bags', 'contain', '3', 'muted', 'indigo', 'bags,', '4', 'clear', 'fuchsia', 'bags,', '4', 'vibrant', 'teal', 'bags,', '5', 'drab', 'violet', 'bags.']\n",
      "['shiny', 'lavender', 'bags', 'contain', '5', 'striped', 'beige', 'bags,', '2', 'dull', 'magenta', 'bags,', '4', 'clear', 'tan', 'bags.']\n",
      "['pale', 'beige', 'bags', 'contain', '5', 'mirrored', 'maroon', 'bags.']\n",
      "['striped', 'bronze', 'bags', 'contain', '1', 'pale', 'orange', 'bag,', '5', 'shiny', 'cyan', 'bags,', '5', 'plaid', 'purple', 'bags,', '1', 'vibrant', 'chartreuse', 'bag.']\n",
      "['faded', 'gold', 'bags', 'contain', '3', 'pale', 'brown', 'bags,', '2', 'dull', 'violet', 'bags,', '2', 'clear', 'maroon', 'bags,', '4', 'dull', 'lime', 'bags.']\n",
      "['clear', 'tomato', 'bags', 'contain', '4', 'vibrant', 'orange', 'bags,', '3', 'bright', 'tomato', 'bags,', '3', 'wavy', 'chartreuse', 'bags,', '5', 'wavy', 'olive', 'bags.']\n",
      "['pale', 'red', 'bags', 'contain', '5', 'wavy', 'blue', 'bags,', '5', 'dark', 'purple', 'bags,', '1', 'bright', 'tomato', 'bag,', '4', 'dark', 'tan', 'bags.']\n",
      "['vibrant', 'red', 'bags', 'contain', '5', 'wavy', 'gray', 'bags,', '5', 'dark', 'tomato', 'bags.']\n",
      "['dim', 'salmon', 'bags', 'contain', '2', 'faded', 'crimson', 'bags.']\n",
      "['shiny', 'blue', 'bags', 'contain', '4', 'muted', 'tan', 'bags,', '2', 'vibrant', 'orange', 'bags.']\n",
      "['vibrant', 'white', 'bags', 'contain', '3', 'mirrored', 'cyan', 'bags.']\n",
      "['dark', 'violet', 'bags', 'contain', '5', 'vibrant', 'blue', 'bags,', '3', 'wavy', 'tomato', 'bags.']\n",
      "['pale', 'gold', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['dim', 'silver', 'bags', 'contain', '4', 'drab', 'tan', 'bags,', '4', 'pale', 'silver', 'bags,', '5', 'clear', 'bronze', 'bags,', '4', 'drab', 'maroon', 'bags.']\n",
      "['drab', 'blue', 'bags', 'contain', '5', 'vibrant', 'indigo', 'bags,', '3', 'muted', 'turquoise', 'bags.']\n",
      "['drab', 'plum', 'bags', 'contain', '2', 'dim', 'turquoise', 'bags,', '2', 'drab', 'violet', 'bags,', '1', 'light', 'gray', 'bag,', '3', 'clear', 'tan', 'bags.']\n",
      "['bright', 'plum', 'bags', 'contain', '3', 'wavy', 'olive', 'bags.']\n",
      "['dark', 'fuchsia', 'bags', 'contain', '4', 'dotted', 'indigo', 'bags,', '3', 'dark', 'brown', 'bags,', '1', 'clear', 'white', 'bag.']\n",
      "['bright', 'turquoise', 'bags', 'contain', '1', 'posh', 'lime', 'bag,', '2', 'wavy', 'olive', 'bags,', '1', 'pale', 'crimson', 'bag.']\n",
      "['dotted', 'turquoise', 'bags', 'contain', '3', 'faded', 'plum', 'bags,', '1', 'bright', 'tomato', 'bag.']\n",
      "['shiny', 'indigo', 'bags', 'contain', '1', 'wavy', 'chartreuse', 'bag.']\n",
      "['dark', 'yellow', 'bags', 'contain', '2', 'light', 'gold', 'bags.']\n",
      "['posh', 'olive', 'bags', 'contain', '2', 'shiny', 'indigo', 'bags.']\n",
      "['light', 'chartreuse', 'bags', 'contain', '5', 'drab', 'turquoise', 'bags,', '2', 'faded', 'purple', 'bags,', '3', 'faded', 'gray', 'bags.']\n",
      "['vibrant', 'tomato', 'bags', 'contain', '3', 'light', 'olive', 'bags,', '4', 'shiny', 'purple', 'bags.']\n",
      "['posh', 'brown', 'bags', 'contain', '4', 'shiny', 'green', 'bags,', '1', 'pale', 'purple', 'bag.']\n",
      "['bright', 'chartreuse', 'bags', 'contain', '3', 'light', 'gold', 'bags.']\n",
      "['dotted', 'lime', 'bags', 'contain', '5', 'wavy', 'cyan', 'bags.']\n",
      "['drab', 'violet', 'bags', 'contain', '4', 'dark', 'beige', 'bags,', '1', 'plaid', 'gold', 'bag,', '3', 'faded', 'beige', 'bags.']\n",
      "['drab', 'green', 'bags', 'contain', '4', 'dotted', 'bronze', 'bags,', '5', 'clear', 'silver', 'bags,', '4', 'faded', 'salmon', 'bags.']\n",
      "['wavy', 'beige', 'bags', 'contain', '2', 'clear', 'cyan', 'bags,', '2', 'dim', 'tomato', 'bags.']\n",
      "['wavy', 'yellow', 'bags', 'contain', '4', 'pale', 'green', 'bags,', '3', 'mirrored', 'green', 'bags,', '5', 'faded', 'brown', 'bags,', '1', 'clear', 'orange', 'bag.']\n",
      "['plaid', 'tomato', 'bags', 'contain', '3', 'dull', 'yellow', 'bags,', '2', 'faded', 'blue', 'bags,', '1', 'dull', 'teal', 'bag.']\n",
      "['dull', 'red', 'bags', 'contain', '4', 'posh', 'green', 'bags,', '1', 'shiny', 'salmon', 'bag,', '2', 'bright', 'tomato', 'bags,', '4', 'vibrant', 'red', 'bags.']\n",
      "['striped', 'salmon', 'bags', 'contain', '4', 'dim', 'bronze', 'bags,', '4', 'light', 'gold', 'bags,', '3', 'posh', 'beige', 'bags.']\n",
      "['dim', 'crimson', 'bags', 'contain', '1', 'dull', 'crimson', 'bag,', '4', 'drab', 'silver', 'bags.']\n",
      "['plaid', 'silver', 'bags', 'contain', '3', 'dull', 'black', 'bags,', '5', 'shiny', 'silver', 'bags,', '4', 'dark', 'beige', 'bags,', '2', 'clear', 'aqua', 'bags.']\n",
      "['clear', 'bronze', 'bags', 'contain', '1', 'drab', 'coral', 'bag,', '2', 'vibrant', 'red', 'bags.']\n",
      "['dotted', 'gray', 'bags', 'contain', '1', 'plaid', 'plum', 'bag,', '2', 'dotted', 'purple', 'bags,', '5', 'striped', 'violet', 'bags,', '3', 'bright', 'tomato', 'bags.']\n",
      "['striped', 'silver', 'bags', 'contain', '2', 'plaid', 'coral', 'bags,', '5', 'bright', 'orange', 'bags,', '1', 'pale', 'brown', 'bag.']\n",
      "['shiny', 'beige', 'bags', 'contain', '4', 'dim', 'turquoise', 'bags.']\n",
      "['posh', 'green', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['plaid', 'gold', 'bags', 'contain', '3', 'pale', 'fuchsia', 'bags,', '5', 'dull', 'lime', 'bags,', '5', 'wavy', 'chartreuse', 'bags,', '5', 'dim', 'tomato', 'bags.']\n",
      "['dim', 'teal', 'bags', 'contain', '5', 'pale', 'beige', 'bags,', '2', 'faded', 'blue', 'bags,', '5', 'dotted', 'tan', 'bags,', '5', 'vibrant', 'tomato', 'bags.']\n",
      "['bright', 'red', 'bags', 'contain', '4', 'drab', 'lavender', 'bags,', '1', 'dark', 'purple', 'bag,', '2', 'wavy', 'violet', 'bags.']\n",
      "['dotted', 'teal', 'bags', 'contain', '5', 'dull', 'crimson', 'bags.']\n",
      "['faded', 'gray', 'bags', 'contain', '4', 'mirrored', 'red', 'bags.']\n",
      "['pale', 'purple', 'bags', 'contain', '3', 'faded', 'gray', 'bags,', '1', 'clear', 'gold', 'bag,', '4', 'clear', 'cyan', 'bags.']\n",
      "['striped', 'crimson', 'bags', 'contain', '4', 'dim', 'aqua', 'bags,', '3', 'pale', 'magenta', 'bags,', '1', 'drab', 'white', 'bag,', '1', 'vibrant', 'purple', 'bag.']\n",
      "['mirrored', 'purple', 'bags', 'contain', '3', 'muted', 'gray', 'bags.']\n",
      "['muted', 'maroon', 'bags', 'contain', '3', 'plaid', 'crimson', 'bags,', '4', 'posh', 'aqua', 'bags.']\n",
      "['muted', 'gold', 'bags', 'contain', '3', 'pale', 'fuchsia', 'bags,', '2', 'dotted', 'teal', 'bags,', '3', 'dotted', 'chartreuse', 'bags,', '4', 'vibrant', 'lime', 'bags.']\n",
      "['wavy', 'silver', 'bags', 'contain', '2', 'plaid', 'beige', 'bags,', '3', 'dull', 'aqua', 'bags,', '2', 'pale', 'lavender', 'bags.']\n",
      "['dim', 'aqua', 'bags', 'contain', '5', 'bright', 'beige', 'bags.']\n",
      "['dark', 'tan', 'bags', 'contain', '4', 'pale', 'gold', 'bags.']\n",
      "['light', 'yellow', 'bags', 'contain', '4', 'dotted', 'gray', 'bags,', '5', 'pale', 'teal', 'bags.']\n",
      "['bright', 'blue', 'bags', 'contain', '3', 'shiny', 'coral', 'bags,', '4', 'striped', 'salmon', 'bags.']\n",
      "['striped', 'cyan', 'bags', 'contain', '5', 'light', 'turquoise', 'bags.']\n",
      "['light', 'gray', 'bags', 'contain', '4', 'vibrant', 'teal', 'bags,', '1', 'shiny', 'turquoise', 'bag,', '1', 'wavy', 'olive', 'bag,', '5', 'dim', 'white', 'bags.']\n",
      "['light', 'cyan', 'bags', 'contain', '3', 'dark', 'gray', 'bags,', '5', 'clear', 'lavender', 'bags,', '4', 'dark', 'beige', 'bags.']\n",
      "['light', 'blue', 'bags', 'contain', '5', 'dim', 'black', 'bags,', '4', 'drab', 'tomato', 'bags,', '2', 'dim', 'turquoise', 'bags.']\n",
      "['dull', 'crimson', 'bags', 'contain', '3', 'pale', 'silver', 'bags,', '2', 'faded', 'beige', 'bags.']\n",
      "['dotted', 'beige', 'bags', 'contain', '2', 'dotted', 'aqua', 'bags.']\n",
      "['shiny', 'olive', 'bags', 'contain', '4', 'bright', 'plum', 'bags,', '4', 'clear', 'plum', 'bags,', '2', 'wavy', 'green', 'bags,', '5', 'faded', 'tomato', 'bags.']\n",
      "['striped', 'turquoise', 'bags', 'contain', '1', 'drab', 'black', 'bag.']\n",
      "['pale', 'chartreuse', 'bags', 'contain', '5', 'dotted', 'brown', 'bags.']\n",
      "['mirrored', 'turquoise', 'bags', 'contain', '4', 'shiny', 'gold', 'bags,', '3', 'dark', 'chartreuse', 'bags.']\n",
      "['posh', 'beige', 'bags', 'contain', '3', 'dotted', 'tan', 'bags.']\n",
      "['drab', 'gray', 'bags', 'contain', '3', 'vibrant', 'aqua', 'bags.']\n",
      "['shiny', 'silver', 'bags', 'contain', '4', 'plaid', 'gold', 'bags,', '5', 'shiny', 'green', 'bags.']\n",
      "['bright', 'crimson', 'bags', 'contain', '5', 'faded', 'yellow', 'bags,', '4', 'bright', 'plum', 'bags,', '4', 'mirrored', 'gold', 'bags.']\n",
      "['dim', 'yellow', 'bags', 'contain', '2', 'plaid', 'lime', 'bags,', '5', 'bright', 'salmon', 'bags,', '4', 'mirrored', 'bronze', 'bags.']\n",
      "['dark', 'crimson', 'bags', 'contain', '4', 'dull', 'blue', 'bags,', '2', 'light', 'olive', 'bags,', '4', 'mirrored', 'green', 'bags.']\n",
      "['faded', 'aqua', 'bags', 'contain', '1', 'dotted', 'chartreuse', 'bag,', '1', 'muted', 'orange', 'bag.']\n",
      "['pale', 'turquoise', 'bags', 'contain', '4', 'dull', 'silver', 'bags.']\n",
      "['clear', 'orange', 'bags', 'contain', '1', 'pale', 'gray', 'bag,', '5', 'striped', 'bronze', 'bags,', '5', 'dim', 'aqua', 'bags.']\n",
      "['mirrored', 'red', 'bags', 'contain', '1', 'muted', 'purple', 'bag.']\n",
      "['drab', 'silver', 'bags', 'contain', 'no', 'other', 'bags.']\n",
      "['faded', 'silver', 'bags', 'contain', '5', 'mirrored', 'turquoise', 'bags,', '4', 'striped', 'purple', 'bags.']\n",
      "['wavy', 'fuchsia', 'bags', 'contain', '2', 'faded', 'purple', 'bags,', '1', 'wavy', 'cyan', 'bag,', '2', 'muted', 'cyan', 'bags.']\n",
      "['clear', 'black', 'bags', 'contain', '4', 'drab', 'turquoise', 'bags,', '1', 'plaid', 'lime', 'bag.']\n",
      "['dim', 'olive', 'bags', 'contain', '5', 'bright', 'chartreuse', 'bags,', '3', 'striped', 'silver', 'bags.']\n",
      "['mirrored', 'tan', 'bags', 'contain', '2', 'striped', 'indigo', 'bags,', '3', 'wavy', 'gray', 'bags,', '3', 'clear', 'tan', 'bags.']\n",
      "['mirrored', 'yellow', 'bags', 'contain', '2', 'plaid', 'plum', 'bags,', '3', 'striped', 'salmon', 'bags,', '4', 'dim', 'maroon', 'bags.']\n",
      "['shiny', 'salmon', 'bags', 'contain', '5', 'dotted', 'plum', 'bags,', '5', 'pale', 'crimson', 'bags.']\n",
      "['dotted', 'crimson', 'bags', 'contain', '3', 'dull', 'yellow', 'bags.']\n",
      "['shiny', 'fuchsia', 'bags', 'contain', '5', 'plaid', 'lime', 'bags.']\n",
      "['drab', 'turquoise', 'bags', 'contain', '2', 'dull', 'crimson', 'bags.']\n",
      "['mirrored', 'cyan', 'bags', 'contain', '3', 'posh', 'green', 'bags,', '5', 'striped', 'olive', 'bags,', '5', 'vibrant', 'red', 'bags.']\n",
      "['faded', 'crimson', 'bags', 'contain', '3', 'muted', 'silver', 'bags,', '4', 'shiny', 'olive', 'bags.']\n",
      "['light', 'magenta', 'bags', 'contain', '3', 'posh', 'crimson', 'bags,', '5', 'pale', 'purple', 'bags.']\n",
      "['faded', 'violet', 'bags', 'contain', '3', 'vibrant', 'lime', 'bags,', '1', 'dim', 'magenta', 'bag,', '1', 'dull', 'lime', 'bag.']\n",
      "['dotted', 'black', 'bags', 'contain', '2', 'light', 'gold', 'bags,', '2', 'dim', 'bronze', 'bags,', '4', 'wavy', 'turquoise', 'bags.']\n",
      "['bright', 'beige', 'bags', 'contain', '4', 'vibrant', 'orange', 'bags,', '4', 'dark', 'chartreuse', 'bags,', '1', 'muted', 'gray', 'bag,', '2', 'bright', 'tomato', 'bags.']\n",
      "['striped', 'green', 'bags', 'contain', '3', 'pale', 'beige', 'bags,', '1', 'pale', 'brown', 'bag,', '2', 'posh', 'brown', 'bags,', '5', 'striped', 'olive', 'bags.']\n",
      "['dotted', 'red', 'bags', 'contain', '4', 'vibrant', 'orange', 'bags,', '2', 'pale', 'gold', 'bags.']\n",
      "['plaid', 'fuchsia', 'bags', 'contain', '5', 'pale', 'teal', 'bags,', '5', 'pale', 'fuchsia', 'bags,', '4', 'faded', 'gray', 'bags.']\n",
      "['light', 'beige', 'bags', 'contain', '1', 'muted', 'red', 'bag,', '5', 'dotted', 'purple', 'bags,', '3', 'striped', 'salmon', 'bags.']\n",
      "['dim', 'chartreuse', 'bags', 'contain', '5', 'muted', 'maroon', 'bags,', '4', 'wavy', 'maroon', 'bags.']\n",
      "['clear', 'chartreuse', 'bags', 'contain', '3', 'striped', 'lavender', 'bags,', '2', 'clear', 'blue', 'bags.']\n",
      "['pale', 'silver', 'bags', 'contain', '2', 'dark', 'teal', 'bags.']\n",
      "['faded', 'olive', 'bags', 'contain', '4', 'dotted', 'turquoise', 'bags,', '4', 'drab', 'indigo', 'bags,', '5', 'drab', 'violet', 'bags,', '3', 'shiny', 'blue', 'bags.']\n",
      "['clear', 'blue', 'bags', 'contain', '1', 'muted', 'black', 'bag.']\n",
      "['dull', 'tan', 'bags', 'contain', '5', 'clear', 'crimson', 'bags,', '3', 'dim', 'tomato', 'bags.']\n",
      "['dark', 'cyan', 'bags', 'contain', '4', 'wavy', 'magenta', 'bags,', '5', 'vibrant', 'olive', 'bags,', '2', 'posh', 'gray', 'bags,', '5', 'dull', 'magenta', 'bags.']\n",
      "['dotted', 'white', 'bags', 'contain', '1', 'bright', 'magenta', 'bag,', '3', 'pale', 'red', 'bags.']\n",
      "['muted', 'teal', 'bags', 'contain', '5', 'posh', 'fuchsia', 'bags,', '4', 'drab', 'turquoise', 'bags,', '4', 'posh', 'red', 'bags.']\n",
      "['mirrored', 'coral', 'bags', 'contain', '1', 'faded', 'purple', 'bag,', '2', 'bright', 'magenta', 'bags,', '5', 'dark', 'yellow', 'bags,', '3', 'light', 'plum', 'bags.']\n",
      "['dull', 'orange', 'bags', 'contain', '4', 'dotted', 'blue', 'bags,', '5', 'clear', 'gray', 'bags,', '3', 'vibrant', 'red', 'bags.']\n",
      "['bright', 'aqua', 'bags', 'contain', '4', 'muted', 'lime', 'bags,', '2', 'wavy', 'plum', 'bags,', '1', 'shiny', 'olive', 'bag.']\n",
      "['light', 'maroon', 'bags', 'contain', '1', 'shiny', 'gold', 'bag,', '4', 'light', 'beige', 'bags,', '1', 'drab', 'black', 'bag.']\n",
      "['dim', 'green', 'bags', 'contain', '4', 'dull', 'brown', 'bags.']\n",
      "['striped', 'black', 'bags', 'contain', '4', 'dotted', 'crimson', 'bags.']\n",
      "['mirrored', 'bronze', 'bags', 'contain', '4', 'mirrored', 'chartreuse', 'bags,', '3', 'dull', 'lime', 'bags,', '3', 'wavy', 'turquoise', 'bags.']\n",
      "['striped', 'aqua', 'bags', 'contain', '4', 'dark', 'gray', 'bags,', '5', 'faded', 'beige', 'bags,', '2', 'dull', 'lime', 'bags.']\n",
      "['shiny', 'coral', 'bags', 'contain', '5', 'mirrored', 'white', 'bags,', '5', 'shiny', 'blue', 'bags.']\n",
      "['striped', 'orange', 'bags', 'contain', '4', 'pale', 'silver', 'bags,', '4', 'pale', 'olive', 'bags,', '4', 'shiny', 'olive', 'bags,', '2', 'bright', 'chartreuse', 'bags.']\n",
      "['vibrant', 'crimson', 'bags', 'contain', '5', 'shiny', 'olive', 'bags,', '5', 'striped', 'violet', 'bags,', '2', 'posh', 'beige', 'bags.']\n",
      "['dotted', 'chartreuse', 'bags', 'contain', '5', 'bright', 'turquoise', 'bags,', '5', 'bright', 'magenta', 'bags.']\n",
      "['vibrant', 'purple', 'bags', 'contain', '4', 'posh', 'violet', 'bags.']\n",
      "['vibrant', 'violet', 'bags', 'contain', '5', 'posh', 'aqua', 'bags,', '4', 'mirrored', 'white', 'bags,', '4', 'dotted', 'tan', 'bags,', '4', 'mirrored', 'purple', 'bags.']\n",
      "['dotted', 'violet', 'bags', 'contain', '3', 'bright', 'brown', 'bags,', '3', 'pale', 'yellow', 'bags,', '4', 'light', 'gray', 'bags,', '5', 'dark', 'green', 'bags.']\n",
      "['muted', 'black', 'bags', 'contain', '2', 'light', 'violet', 'bags,', '5', 'muted', 'bronze', 'bags.']\n",
      "['mirrored', 'orange', 'bags', 'contain', '1', 'plaid', 'magenta', 'bag,', '5', 'muted', 'red', 'bags,', '3', 'pale', 'lime', 'bags.']\n",
      "['faded', 'magenta', 'bags', 'contain', '3', 'striped', 'cyan', 'bags,', '4', 'muted', 'silver', 'bags.']\n",
      "['clear', 'gray', 'bags', 'contain', '4', 'muted', 'gray', 'bags,', '2', 'wavy', 'turquoise', 'bags,', '3', 'dotted', 'plum', 'bags.']\n"
     ]
    }
   ],
   "source": [
    "colors = []\n",
    "\n",
    "for rule in rules : \n",
    "    rule = rule.split(' ')\n",
    "    print(rule)\n",
    "    for word in range(len(rule)) :\n",
    "        if 'bag' in rule[word] : \n",
    "            colors.append(rule[word-2]+' '+rule[word-1])\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The idea is to create a graph, the steps are : \n",
    "* First, identify for each rule, the number of bags this rule applies to\n",
    "* If more than one bag is concerned (if it is not an end), identify which colors are mentioned and the number of bags they can contain\n",
    "* The first mentioned is the container and the other(s) are contained\n",
    "* Then add a new connection to the graph "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 814,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dict to directly draw graph\n",
    "graph = {}\n",
    "\n",
    "for rule in rules : \n",
    "    rule = rule.split(' ')\n",
    "    container = ''\n",
    "    colors_bags = []\n",
    "    numbers_bags = []\n",
    "    for word in range(len(rule)) :\n",
    "        if 'bag' in rule[word] : \n",
    "            if container == '':\n",
    "                container = rule[word-2]+' '+rule[word-1]\n",
    "            elif rule[word-2]+' '+rule[word-1] == 'no other' : \n",
    "                pass\n",
    "            else : \n",
    "                colors_bags.append(rule[word-2]+' '+rule[word-1])\n",
    "                numbers_bags.append(rule[word-3])\n",
    "    \n",
    "    graph[container] = colors_bags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 815,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Array containing all edges of the graphs -> easier to include weights\n",
    "edges = []\n",
    "\n",
    "for rule in rules : \n",
    "    rule = rule.split(' ')\n",
    "    container = ''\n",
    "    colors_bags = []\n",
    "    numbers_bags = []\n",
    "    for word in range(len(rule)) :\n",
    "        if 'bag' in rule[word] : \n",
    "            if container == '':\n",
    "                container = rule[word-2]+' '+rule[word-1]\n",
    "            elif rule[word-2]+' '+rule[word-1] == 'no other' : \n",
    "                pass\n",
    "            else : \n",
    "                color = rule[word-2]+' '+rule[word-1]\n",
    "                number = rule[word-3]\n",
    "                edges.append( [container, color, number] )\n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 843,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_graph_from_array(edges):\n",
    "    G = nx.DiGraph()\n",
    "    \n",
    "    for edge in edges : \n",
    "        G.add_edge(edge[0], edge[1], weight= edge[2])\n",
    "    \n",
    "    return G\n",
    "\n",
    "def display_graph(G, method = nx.circular_layout):\n",
    "    \n",
    "    plt.figure(figsize=(20,15))\n",
    "\n",
    "    options = {\n",
    "        \"font_size\": 10,\n",
    "        \"node_size\": 6000,\n",
    "        \"node_color\": \"white\",\n",
    "        \"edgecolors\": \"black\",\n",
    "        \"linewidths\": 2,\n",
    "        \"width\": 2,\n",
    "    }\n",
    "\n",
    "\n",
    "    pos = method(G)  # positions for all nodes\n",
    "\n",
    "    nx.draw(G,pos, **options)\n",
    "    labels = nx.get_edge_attributes(G,'weight')\n",
    "    nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)\n",
    "\n",
    "    # labels\n",
    "    nx.draw_networkx_labels(G, pos, font_size=10, font_family=\"sans-serif\")\n",
    "\n",
    "    plt.axis(\"off\")\n",
    "    plt.show()\n",
    "    \n",
    "def get_roots(G):\n",
    "    roots = []\n",
    "    for node in G.nodes :\n",
    "        if G.in_degree(node) == 0 : # it's a root\n",
    "            roots.append(node)\n",
    "    return roots\n",
    "\n",
    "def get_leafs(G):\n",
    "    leafs = []\n",
    "    for node in G.nodes :\n",
    "        if G.out_degree(node) == 0 : # it's a root\n",
    "            leafs.append(node)\n",
    "    return leafs\n",
    "\n",
    "def get_paths_to(graph, node):\n",
    "    roots = get_roots(graph)\n",
    "    paths = []\n",
    "    for root in roots : \n",
    "        for path in nx.all_simple_paths(graph,root,node) :\n",
    "            paths.append(path)\n",
    "    return paths\n",
    "\n",
    "def get_paths_from(graph, node):\n",
    "    leafs = get_leafs(graph)\n",
    "    paths = []\n",
    "    for leaf in leafs : \n",
    "        for path in nx.all_simple_paths(graph,node,leaf) :\n",
    "            paths.append(path)\n",
    "    return paths\n",
    "\n",
    "def path_to_weights(graph, path):\n",
    "    assert len(path)>1,'path contains only one bag'\n",
    "    \n",
    "    weights = [0]\n",
    "    for bag in range(len(path)-1):\n",
    "        weights.append( int(graph.get_edge_data(path[bag],path[bag+1],'weight')['weight']) ) \n",
    "    \n",
    "    return weights\n",
    "\n",
    "\n",
    "def path_to_number_of_bags(graph,path):\n",
    "    assert len(path)>1,'path contains only one bag'\n",
    "    \n",
    "    weight = path_to_weights(graph, path)\n",
    "    summ = 0\n",
    "    mul = 1\n",
    "    for i in range(1,len(weight)):\n",
    "        mul *= weight[i]\n",
    "        summ += mul\n",
    "    return summ\n",
    "\n",
    "def find_common_path(path1, path2):\n",
    "    common_path = []\n",
    "    bag = 0\n",
    "    while( path1[bag]==path2[bag] and bag < min(len(path1),len(path2)) ):\n",
    "        common_path.append(path1[bag])\n",
    "        bag += 1\n",
    "    return common_path\n",
    "\n",
    "def doubled_paths(paths):\n",
    "    doubled = []\n",
    "    for i in range(len(paths)-1):\n",
    "        for j in range(i+1,len(paths)):\n",
    "            common = find_common_path(paths[i],paths[j])\n",
    "        \n",
    "            if len(common) > 1: doubled.append(common)\n",
    "    return doubled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 817,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = create_graph_from_array(edges)\n",
    "#G.add_edge('dark blue', 'copain', weight= 2)\n",
    "#display_graph(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 818,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of bags that could contain shiny gold is 272\n"
     ]
    }
   ],
   "source": [
    "bag = 'shiny gold'\n",
    "\n",
    "paths = get_paths_to(G, bag)\n",
    "all_bags_in_paths =  [item for sublist in paths for item in sublist]\n",
    "unique_bags = np.unique(all_bags_in_paths) # contains the bag of interest ! \n",
    "if unique_bags.shape[0]-1 >0 :\n",
    "    num_containers = unique_bags.shape[0]-1\n",
    "else :\n",
    "    num_containers = 0\n",
    "print('The number of bags that could contain {} is {}'.format(bag,num_containers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 823,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'striped olive'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'striped olive'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'striped olive'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'striped olive'], ['shiny gold', 'mirrored maroon', 'striped olive'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'striped olive'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'drab silver'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'drab silver'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'drab silver'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'drab silver'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'drab silver'], ['shiny gold', 'bright beige', 'dark chartreuse', 'shiny blue', 'muted tan'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'muted tan'], ['shiny gold', 'dull crimson', 'faded beige', 'shiny blue', 'muted tan'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'muted tan'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive', 'muted tan'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'muted tan'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive', 'muted tan'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'muted tan'], ['shiny gold', 'bright beige', 'muted gray', 'posh green'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'muted gray', 'posh green'], ['shiny gold', 'bright beige', 'bright tomato', 'muted gray', 'posh green'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'muted gray', 'posh green'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'muted gray', 'posh green'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'muted gray', 'posh green'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'muted gray', 'posh green'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'muted gray', 'posh green'], ['shiny gold', 'bright tomato', 'muted gray', 'posh green'], ['shiny gold', 'bright beige', 'vibrant orange'], ['shiny gold', 'bright beige', 'dark chartreuse', 'shiny blue', 'vibrant orange'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'vibrant orange'], ['shiny gold', 'dull crimson', 'faded beige', 'shiny blue', 'vibrant orange'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'vibrant orange'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'vibrant orange'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'vibrant orange'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'vibrant orange'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'dull crimson', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'pale crimson'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'dark tomato'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'dark tomato'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'dark tomato'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'dark tomato'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'dark tomato'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'dark tomato'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive', 'dark tomato'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'dark tomato'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive', 'dark tomato'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'dark tomato'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'dark tomato'], ['shiny gold', 'bright tomato', 'vibrant red', 'dark tomato'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'dull crimson', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal', 'wavy olive'], ['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'pale gold'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'pale gold'], ['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive', 'pale gold'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'pale gold'], ['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive', 'pale gold'], ['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive', 'pale gold'], ['shiny gold', 'mirrored maroon', 'pale lime']]\n"
     ]
    }
   ],
   "source": [
    "bag = 'shiny gold'\n",
    "\n",
    "paths = get_paths_from(G, bag)\n",
    "weights = [path_to_weights(G, path) for path in paths]\n",
    "\n",
    "\n",
    "print( paths)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 825,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test = create_graph_from_array(paths)\n",
    "display_graph(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 820,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "219267\n"
     ]
    }
   ],
   "source": [
    "summ = 0\n",
    "for path in paths:\n",
    "    summ += path_to_number_of_bags(G, path)\n",
    "print(summ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 845,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "126142\n"
     ]
    }
   ],
   "source": [
    "doubled_summ = 0\n",
    "for path in doubled_paths(paths) : \n",
    "    doubled_summ += path_to_number_of_bags(G, path)\n",
    "\n",
    "print(doubled_summ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 855,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'dark chartreuse', 'shiny blue'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'shiny blue'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon', 'bright magenta'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n",
      "['shiny gold', 'mirrored maroon'] \n",
      "----------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "doubled = doubled_paths(paths)\n",
    "for i in range(len(doubled)):\n",
    "    print(doubled[i],'\\n----------------\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 893,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[list(['shiny gold', 'bright beige'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato', 'vibrant red'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'])\n",
      " list(['shiny gold', 'bright beige', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'])\n",
      " list(['shiny gold', 'bright beige', 'dark chartreuse', 'shiny blue'])\n",
      " list(['shiny gold', 'bright tomato'])\n",
      " list(['shiny gold', 'bright tomato', 'vibrant red'])\n",
      " list(['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray'])\n",
      " list(['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan'])\n",
      " list(['shiny gold', 'bright tomato', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'])\n",
      " list(['shiny gold', 'dull crimson'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'vibrant red', 'wavy gray', 'wavy cyan', 'vibrant olive'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'plaid lime', 'wavy gray', 'wavy cyan', 'vibrant olive'])\n",
      " list(['shiny gold', 'dull crimson', 'faded beige', 'shiny blue'])\n",
      " list(['shiny gold', 'dull crimson', 'pale silver', 'dark teal'])\n",
      " list(['shiny gold', 'mirrored maroon'])\n",
      " list(['shiny gold', 'mirrored maroon', 'bright magenta'])\n",
      " list(['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan'])\n",
      " list(['shiny gold', 'mirrored maroon', 'bright magenta', 'wavy cyan', 'vibrant olive'])]\n"
     ]
    }
   ],
   "source": [
    "doubled = np.unique(doubled)\n",
    "print(doubled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 860,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = []\n",
    "\n",
    "for i in range(len(doubled)):\n",
    "    to_append = ''\n",
    "    for j in range(len(doubled[i])):\n",
    "        to_append += doubled[i][j]+' '\n",
    "    to_append = to_append[:-1]\n",
    "    test.append(to_append)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 861,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>shiny gold bright beige bright tomato vibrant ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>shiny gold bright beige</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>shiny gold bright beige bright tomato vibrant ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>shiny gold bright beige</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>shiny gold bright beige bright tomato vibrant ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>shiny gold bright tomato vibrant red wavy gray</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>615</th>\n",
       "      <td>shiny gold dull crimson faded beige plaid lime</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>616</th>\n",
       "      <td>shiny gold mirrored maroon bright magenta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>shiny gold mirrored maroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>618</th>\n",
       "      <td>shiny gold mirrored maroon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>619 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  data\n",
       "0    shiny gold bright beige bright tomato vibrant ...\n",
       "1                              shiny gold bright beige\n",
       "2    shiny gold bright beige bright tomato vibrant ...\n",
       "3                              shiny gold bright beige\n",
       "4    shiny gold bright beige bright tomato vibrant ...\n",
       "..                                                 ...\n",
       "614     shiny gold bright tomato vibrant red wavy gray\n",
       "615     shiny gold dull crimson faded beige plaid lime\n",
       "616          shiny gold mirrored maroon bright magenta\n",
       "617                         shiny gold mirrored maroon\n",
       "618                         shiny gold mirrored maroon\n",
       "\n",
       "[619 rows x 1 columns]"
      ]
     },
     "execution_count": 861,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = pd.DataFrame(test,columns=['data'])\n",
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 890,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-890-a5ad68726cf7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mind2\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m         \u001b[0;31m#print(ind,ind2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m         \u001b[0;32mif\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mind2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mto_drop\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mto_drop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m                 \u001b[0;31m#print()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1765\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1766\u001b[0m             \u001b[0mmaybe_callable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1767\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmaybe_callable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1768\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1769\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1962\u001b[0m         \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1963\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1964\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1965\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1966\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_label\u001b[0;34m(self, label, axis)\u001b[0m\n\u001b[1;32m    622\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"no slices here, handle elsewhere\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    623\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 624\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_xs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    625\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    626\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mxs\u001b[0;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[1;32m   3513\u001b[0m         \"\"\"\n\u001b[1;32m   3514\u001b[0m         \u001b[0maxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis_number\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3515\u001b[0;31m         \u001b[0mlabels\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3516\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlevel\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3517\u001b[0m             \u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_ax\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc_level\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdrop_level\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdrop_level\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "to_drop = []\n",
    "index = test.index\n",
    "for ind in range(len(index)):\n",
    "    for ind2 in range(ind,len(index)):\n",
    "        #print(ind,ind2)\n",
    "        if test.loc[index[ind]][0] in test.loc[index[ind2]][0] : \n",
    "            if index[ind] not in to_drop : to_drop.append(index[ind])\n",
    "                #print()\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 891,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]\n"
     ]
    }
   ],
   "source": [
    "print(to_drop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 697,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "12\n",
      "13\n",
      "26\n",
      "55\n"
     ]
    }
   ],
   "source": [
    "path = 0\n",
    "summ = 0\n",
    "for path in paths: \n",
    "    summ += path_to_number_of_bags(G,path)\n",
    "    print( path_to_number_of_bags(G,path) )\n",
    "    \n",
    "print(summ)\n",
    "\n",
    "def ugly_trick(graph, paths):\n",
    "    delt = []\n",
    "    sous = 0\n",
    "    for path in paths : \n",
    "        if path[1] not in delt :\n",
    "            sous += int(graph.get_edge_data(path[0],path[1],'weight')['weight'])\n",
    "            delt.append(path[1])\n",
    "    return sous "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 826,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_edges = []\n",
    "for path in paths :\n",
    "    for ind in range(len(path)-1):\n",
    "        sub_edges.append( [path[ind],path[ind+1],int(G.get_edge_data(path[ind],path[ind+1])['weight'])] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 827,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'striped olive', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'striped olive', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'striped olive', 4],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'striped olive', 4],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'striped olive', 3],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'striped olive', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'drab silver', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'drab silver', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'drab silver', 4],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'drab silver', 4],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'drab silver', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'dark chartreuse', 4],\n",
       " ['dark chartreuse', 'shiny blue', 5],\n",
       " ['shiny blue', 'muted tan', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'muted tan', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'shiny blue', 1],\n",
       " ['shiny blue', 'muted tan', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'muted tan', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'muted tan', 4],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'muted tan', 2],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'muted tan', 4],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'muted tan', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'muted gray', 1],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'muted gray', 2],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'muted gray', 3],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'muted gray', 3],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'muted gray', 2],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'muted gray', 2],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'muted gray', 2],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'muted gray', 2],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'muted gray', 3],\n",
       " ['muted gray', 'posh green', 2],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'vibrant orange', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'dark chartreuse', 4],\n",
       " ['dark chartreuse', 'shiny blue', 5],\n",
       " ['shiny blue', 'vibrant orange', 2],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'vibrant orange', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'shiny blue', 1],\n",
       " ['shiny blue', 'vibrant orange', 2],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'vibrant orange', 4],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'vibrant orange', 4],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'vibrant orange', 4],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'vibrant orange', 4],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'pale silver', 3],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'pale silver', 1],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'pale crimson', 3],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'dark tomato', 5],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'dark tomato', 2],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'dark tomato', 5],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'dark tomato', 5],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'dark tomato', 2],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'dark tomato', 5],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'dark tomato', 5],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'dark tomato', 2],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'dark tomato', 5],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'dark tomato', 5],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'dark tomato', 2],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'dark tomato', 5],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'pale silver', 3],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'pale silver', 1],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'pale silver', 5],\n",
       " ['pale silver', 'dark teal', 2],\n",
       " ['dark teal', 'wavy olive', 3],\n",
       " ['shiny gold', 'bright beige', 4],\n",
       " ['bright beige', 'bright tomato', 2],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'pale gold', 1],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'vibrant red', 5],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'pale gold', 1],\n",
       " ['shiny gold', 'dull crimson', 3],\n",
       " ['dull crimson', 'faded beige', 2],\n",
       " ['faded beige', 'plaid lime', 5],\n",
       " ['plaid lime', 'wavy gray', 1],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'pale gold', 1],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'pale gold', 1],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'bright magenta', 3],\n",
       " ['bright magenta', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'pale gold', 1],\n",
       " ['shiny gold', 'bright tomato', 3],\n",
       " ['bright tomato', 'vibrant red', 3],\n",
       " ['vibrant red', 'wavy gray', 5],\n",
       " ['wavy gray', 'wavy cyan', 2],\n",
       " ['wavy cyan', 'vibrant olive', 3],\n",
       " ['vibrant olive', 'pale gold', 1],\n",
       " ['shiny gold', 'mirrored maroon', 4],\n",
       " ['mirrored maroon', 'pale lime', 5]]"
      ]
     },
     "execution_count": 827,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_edges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 837,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test = create_graph_from_array(sub_edges)\n",
    "\n",
    "display_graph(test, method = nx.circular_layout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 556,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(284,)"
      ]
     },
     "execution_count": 556,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_bags.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = [1,3,5,6]\n",
    "print( [mul for mul] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['light red', 'bright white', 'shiny gold']\n",
      "['light red', 'muted yellow', 'shiny gold']\n",
      "['dark orange', 'bright white', 'shiny gold']\n",
      "['dark orange', 'muted yellow', 'shiny gold']\n"
     ]
    }
   ],
   "source": [
    "bags = []\n",
    "summ = 0\n",
    "for root in roots : \n",
    "    for path in nx.all_simple_paths(G,root,'shiny gold') :\n",
    "        print(path)\n",
    "        bags.append(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 687,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['shiny gold', 'dark olive', 'faded blue'],\n",
       " ['shiny gold', 'dark olive', 'dotted black'],\n",
       " ['shiny gold', 'vibrant plum', 'faded blue'],\n",
       " ['shiny gold', 'vibrant plum', 'dotted black']]"
      ]
     },
     "execution_count": 687,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "roots = (v for v, d in test.in_degree() if d == 0)\n",
    "leaves = [v for v, d in test.out_degree() if d == 0]\n",
    "all_paths = []\n",
    "for root in roots:\n",
    "    paths = nx.all_simple_paths(test, root, leaves)\n",
    "    all_paths.extend(paths)\n",
    "all_paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 686,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_graph(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 689,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for +: 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-689-417eddf8f07d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlen_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mall_pairs_dijkstra\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'weight'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mnodes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/networkx/algorithms/shortest_paths/weighted.py\u001b[0m in \u001b[0;36mall_pairs_dijkstra\u001b[0;34m(G, cutoff, weight)\u001b[0m\n\u001b[1;32m    983\u001b[0m     \"\"\"\n\u001b[1;32m    984\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mG\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 985\u001b[0;31m         \u001b[0mdist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msingle_source_dijkstra\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcutoff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcutoff\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    986\u001b[0m         \u001b[0;32myield\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    987\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/networkx/algorithms/shortest_paths/weighted.py\u001b[0m in \u001b[0;36msingle_source_dijkstra\u001b[0;34m(G, source, target, cutoff, weight)\u001b[0m\n\u001b[1;32m    463\u001b[0m     \"\"\"\n\u001b[1;32m    464\u001b[0m     return multi_source_dijkstra(\n\u001b[0;32m--> 465\u001b[0;31m         \u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcutoff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcutoff\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    466\u001b[0m     )\n\u001b[1;32m    467\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/networkx/algorithms/shortest_paths/weighted.py\u001b[0m in \u001b[0;36mmulti_source_dijkstra\u001b[0;34m(G, sources, target, cutoff, weight)\u001b[0m\n\u001b[1;32m    721\u001b[0m     \u001b[0mpaths\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msource\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msources\u001b[0m\u001b[0;34m}\u001b[0m  \u001b[0;31m# dictionary of paths\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    722\u001b[0m     dist = _dijkstra_multisource(\n\u001b[0;32m--> 723\u001b[0;31m         \u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msources\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpaths\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpaths\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcutoff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcutoff\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtarget\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    724\u001b[0m     )\n\u001b[1;32m    725\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mtarget\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/fieldbox/lib/python3.7/site-packages/networkx/algorithms/shortest_paths/weighted.py\u001b[0m in \u001b[0;36m_dijkstra_multisource\u001b[0;34m(G, sources, weight, pred, paths, cutoff, target)\u001b[0m\n\u001b[1;32m    822\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mcost\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    823\u001b[0m                 \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 824\u001b[0;31m             \u001b[0mvu_dist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdist\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mcost\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    825\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mcutoff\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    826\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mvu_dist\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0mcutoff\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "len_path = dict(nx.all_pairs_dijkstra(G, weight='weight'))\n",
    "\n",
    "nodes = list(G.nodes())\n",
    "results = pd.DataFrame()\n",
    "\n",
    "starting_point = []\n",
    "for i in range(len(nodes)):\n",
    "    results = results.append(pd.DataFrame(len_path[nodes[i]]).T.reset_index())\n",
    "    starting_point = starting_point + [nodes[i]]*len(len_path[nodes[i]][1])\n",
    "\n",
    "\n",
    "paths_df = pd.DataFrame()\n",
    "paths_df['starting_point'] = starting_point\n",
    "\n",
    "results.columns = ['ending_point','weight','path']\n",
    "results = results.reset_index()\n",
    "del results['index']\n",
    "\n",
    "results = pd.concat((paths_df,results),axis=1)\n",
    "\n",
    "print(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 693,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 693,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.node_connectivity(G,s='shiny gold',t= 'dotted black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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